1
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Murase Y, Hilbe C. Computational evolution of social norms in well-mixed and group-structured populations. Proc Natl Acad Sci U S A 2024; 121:e2406885121. [PMID: 39116135 PMCID: PMC11331111 DOI: 10.1073/pnas.2406885121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 07/15/2024] [Indexed: 08/10/2024] Open
Abstract
Models of indirect reciprocity study how social norms promote cooperation. In these models, cooperative individuals build up a positive reputation, which in turn helps them in their future interactions. The exact reputational benefits of cooperation depend on the norm in place, which may change over time. Previous research focused on the stability of social norms. Much less is known about how social norms initially evolve when competing with many others. A comprehensive evolutionary analysis, however, has been difficult. Even among the comparably simple space of so-called third-order norms, there are thousands of possibilities, each one inducing its own reputation dynamics. To address this challenge, we use large-scale computer simulations. We study the reputation dynamics of each third-order norm and all evolutionary transitions between them. In contrast to established work with only a handful of norms, we find that cooperation is hard to maintain in well-mixed populations. However, within group-structured populations, cooperation can emerge. The most successful norm in our simulations is particularly simple. It regards cooperation as universally positive, and defection as usually negative-unless defection takes the form of justified punishment. This research sheds light on the complex interplay of social norms, their induced reputation dynamics, and population structure.
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Affiliation(s)
- Yohsuke Murase
- RIKEN Center for Computational Science, Kobe650-0047, Japan
| | - Christian Hilbe
- Max Planck Research Group Dynamics of Social Behavior, Max Planck Institute for Evolutionary Biology, Plön24306, Germany
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2
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Okada I, De Silva H. Norms prioritizing positive assessments are likely to maintain cooperation in private indirect reciprocity. Sci Rep 2024; 14:17264. [PMID: 39068170 PMCID: PMC11283462 DOI: 10.1038/s41598-024-67773-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 07/15/2024] [Indexed: 07/30/2024] Open
Abstract
Exploring the evolutionary mechanisms of cooperation in societies where reputational consensus cannot be assumed, as in divided societies, is important for understanding the basic principles of human behavior in modern societies. Indirect reciprocity provides a major explanatory mechanism, but most studies have focused on how donors, i.e., one who decides whether to donate (cooperate or help) to a recipient or do nothing, are assessed. It is natural to think that there is no consensus among assessors in our society, and there is no reason to update only donor assessments when updating assessments. We constructed an agent-based model that enables updating of both donors' and recipients' images. Our exhaustive simulations showed that the well analyzed assessment rules updating donors' images are only second best to an assessment rule updating bad images in most likely for maintaining cooperative regimes. Such a social norm that prioritizes a positive assessment is considered tolerant, which is also consistent with previous studies arguing that tolerant evaluation is important in private-assessment schemes.
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Affiliation(s)
- Isamu Okada
- Faculty of Business Administration, Soka University, Hachioji, 192-8577, Japan.
- Research Institute for Cryptoeconomics, WU - Vienna University of Economics and Business, 1020, Vienna, Austria.
| | - Hannelore De Silva
- Institute for Finance, Banking and Insurance, WU - Vienna University of Economics and Business, 1020, Vienna, Austria
- Research Institute for Cryptoeconomics, WU - Vienna University of Economics and Business, 1020, Vienna, Austria
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3
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Cavaliere M, Yang G, De Dreu CKW, Gross J. Cooperation and social organization depend on weighing private and public reputations. Sci Rep 2024; 14:16443. [PMID: 39014019 PMCID: PMC11252375 DOI: 10.1038/s41598-024-67080-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 07/08/2024] [Indexed: 07/18/2024] Open
Abstract
To avoid exploitation by defectors, people can use past experiences with others when deciding to cooperate or not ('private information'). Alternatively, people can derive others' reputation from 'public' information provided by individuals within the social network. However, public information may be aligned or misaligned with one's own private experiences and different individuals, such as 'friends' and 'enemies', may have different opinions about the reputation of others. Using evolutionary agent-based simulations, we examine how cooperation and social organization is shaped when agents (1) prioritize private or public information about others' reputation, and (2) integrate others' opinions using a friend-focused or a friend-and-enemy focused heuristic (relying on reputation information from only friends or also enemies, respectively). When agents prioritize public information and rely on friend-and-enemy heuristics, we observe polarization cycles marked by high cooperation, invasion by defectors, and subsequent population fragmentation. Prioritizing private information diminishes polarization and defector invasions, but also results in limited cooperation. Only when using friend-focused heuristics and following past experiences or the recommendation of friends create prosperous and stable populations based on cooperation. These results show how combining one's own experiences and the opinions of friends can lead to stable and large-scale cooperation and highlight the important role of following the advice of friends in the evolution of group cooperation.
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Affiliation(s)
- Matteo Cavaliere
- Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, Modena, Italy.
| | - Guoli Yang
- Department of Big Data Intelligence, Advanced Institute of Big Data, Beijing, 100195, China
| | - Carsten K W De Dreu
- Faculty of Behavioral and Social Sciences, University of Groningen, Groningen, The Netherlands
- Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands
- Behavioral Ecology and Sociobiology Unit, German Primate Center, Leibniz Institute for Primate Research, Göttingen, Germany
| | - Jörg Gross
- Department of Psychology, University of Zurich, Zurich, Switzerland
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4
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Kawakatsu M, Kessinger TA, Plotkin JB. A mechanistic model of gossip, reputations, and cooperation. Proc Natl Acad Sci U S A 2024; 121:e2400689121. [PMID: 38717858 PMCID: PMC11098103 DOI: 10.1073/pnas.2400689121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/12/2024] [Indexed: 05/18/2024] Open
Abstract
Social reputations facilitate cooperation: those who help others gain a good reputation, making them more likely to receive help themselves. But when people hold private views of one another, this cycle of indirect reciprocity breaks down, as disagreements lead to the perception of unjustified behavior that ultimately undermines cooperation. Theoretical studies often assume population-wide agreement about reputations, invoking rapid gossip as an endogenous mechanism for reaching consensus. However, the theory of indirect reciprocity lacks a mechanistic description of how gossip actually generates consensus. Here, we develop a mechanistic model of gossip-based indirect reciprocity that incorporates two alternative forms of gossip: exchanging information with randomly selected peers or consulting a single gossip source. We show that these two forms of gossip are mathematically equivalent under an appropriate transformation of parameters. We derive an analytical expression for the minimum amount of gossip required to reach sufficient consensus and stabilize cooperation. We analyze how the amount of gossip necessary for cooperation depends on the benefits and costs of cooperation, the assessment rule (social norm), and errors in reputation assessment, strategy execution, and gossip transmission. Finally, we show that biased gossip can either facilitate or hinder cooperation, depending on the direction and magnitude of the bias. Our results contribute to the growing literature on cooperation facilitated by communication, and they highlight the need to study strategic interactions coupled with the spread of social information.
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Affiliation(s)
- Mari Kawakatsu
- Department of Biology, University of Pennsylvania, Philadelphia, PA19104
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA19104
| | | | - Joshua B. Plotkin
- Department of Biology, University of Pennsylvania, Philadelphia, PA19104
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA19104
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5
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Schnell E, Muthukrishna M. Indirect reciprocity undermines indirect reciprocity destabilizing large-scale cooperation. Proc Natl Acad Sci U S A 2024; 121:e2322072121. [PMID: 38683991 PMCID: PMC11087788 DOI: 10.1073/pnas.2322072121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/01/2024] [Indexed: 05/02/2024] Open
Abstract
Previous models suggest that indirect reciprocity (reputation) can stabilize large-scale human cooperation [K. Panchanathan, R. Boyd, Nature 432, 499-502 (2004)]. The logic behind these models and experiments [J. Gross et al., Sci. Adv. 9, eadd8289 (2023) and O. P. Hauser, A. Hendriks, D. G. Rand, M. A. Nowak, Sci. Rep. 6, 36079 (2016)] is that a strategy in which individuals conditionally aid others based on their reputation for engaging in costly cooperative behavior serves as a punishment that incentivizes large-scale cooperation without the second-order free-rider problem. However, these models and experiments fail to account for individuals belonging to multiple groups with reputations that can be in conflict. Here, we extend these models such that individuals belong to a smaller, "local" group embedded within a larger, "global" group. This introduces competing strategies for conditionally aiding others based on their cooperative behavior in the local or global group. Our analyses reveal that the reputation for cooperation in the smaller local group can undermine cooperation in the larger global group, even when the theoretical maximum payoffs are higher in the larger global group. This model reveals that indirect reciprocity alone is insufficient for stabilizing large-scale human cooperation because cooperation at one scale can be considered defection at another. These results deepen the puzzle of large-scale human cooperation.
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Affiliation(s)
- Eric Schnell
- Department of Psychological and Behavioural Science, London School of Economics and Political Science, LondonWC2A 2AE, United Kingdom
| | - Michael Muthukrishna
- Department of Psychological and Behavioural Science, London School of Economics and Political Science, LondonWC2A 2AE, United Kingdom
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6
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Meng Y, Cornelius SP, Liu YY, Li A. Dynamics of collective cooperation under personalised strategy updates. Nat Commun 2024; 15:3125. [PMID: 38600076 PMCID: PMC11006938 DOI: 10.1038/s41467-024-47380-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 03/28/2024] [Indexed: 04/12/2024] Open
Abstract
Collective cooperation is essential for many social and biological systems, yet understanding how it evolves remains a challenge. Previous investigations report that the ubiquitous heterogeneous individual connections hinder cooperation by assuming individuals update strategies at identical rates. Here we develop a general framework by allowing individuals to update strategies at personalised rates, and provide the precise mathematical condition under which universal cooperation is favoured. Combining analytical and numerical calculations on synthetic and empirical networks, we find that when individuals' update rates vary inversely with their number of connections, heterogeneous connections actually outperform homogeneous ones in promoting cooperation. This surprising property undercuts the conventional wisdom that heterogeneous structure is generally antagonistic to cooperation and, further helps develop an efficient algorithm OptUpRat to optimise collective cooperation by designing individuals' update rates in any population structure. Our findings provide a unifying framework to understand the interplay between structural heterogeneity, behavioural rhythms, and cooperation.
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Affiliation(s)
- Yao Meng
- Center for Systems and Control, College of Engineering, Peking University, Beijing, 100871, China
| | - Sean P Cornelius
- Department of Physics, Toronto Metropolitan University, Toronto, ON, M5B 2K3, Canada
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, 61801, USA
| | - Aming Li
- Center for Systems and Control, College of Engineering, Peking University, Beijing, 100871, China.
- Center for Multi-Agent Research, Institute for Artificial Intelligence, Peking University, Beijing, 100871, China.
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7
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Kawakatsu M, Michel-Mata S, Kessinger TA, Tarnita CE, Plotkin JB. When do stereotypes undermine indirect reciprocity? PLoS Comput Biol 2024; 20:e1011862. [PMID: 38427626 PMCID: PMC10906830 DOI: 10.1371/journal.pcbi.1011862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 01/28/2024] [Indexed: 03/03/2024] Open
Abstract
Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.
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Affiliation(s)
- Mari Kawakatsu
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Sebastián Michel-Mata
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Taylor A. Kessinger
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Corina E. Tarnita
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Joshua B. Plotkin
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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8
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De Dreu CKW, Gross J, Romano A. Group Formation and the Evolution of Human Social Organization. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2024; 19:320-334. [PMID: 37450408 PMCID: PMC10913362 DOI: 10.1177/17456916231179156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Humans operate in groups that are oftentimes nested in multilayered collectives such as work units within departments and companies, neighborhoods within cities, and regions within nation states. With psychological science mostly focusing on proximate reasons for individuals to join existing groups and how existing groups function, we still poorly understand why groups form ex nihilo, how groups evolve into complex multilayered social structures, and what explains fission-fusion dynamics. Here we address group formation and the evolution of social organization at both the proximate and ultimate level of analysis. Building on models of fitness interdependence and cooperation, we propose that socioecologies can create positive interdependencies among strangers and pave the way for the formation of stable coalitions and groups through reciprocity and reputation-based partner selection. Such groups are marked by in-group bounded, parochial cooperation together with an array of social institutions for managing the commons, allowing groups to scale in size and complexity while avoiding the breakdown of cooperation. Our analysis reveals how distinct group cultures can endogenously emerge from reciprocal cooperation, shows that social identification and group commitment are likely consequences rather than causes of group cooperation, and explains when intergroup relations gravitate toward peaceful coexistence, integration, or conflict.
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Affiliation(s)
| | - Jörg Gross
- Department of Psychology, University of Zurich
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9
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Abstract
Reputation and reciprocity are key mechanisms for cooperation in human societies, often going hand in hand to favor prosocial behavior over selfish actions. Here we review recent researches at the interface of physics and evolutionary game theory that explored these two mechanisms. We focus on image scoring as the bearer of reputation, as well as on various types of reciprocity, including direct, indirect, and network reciprocity. We review different definitions of reputation and reciprocity dynamics, and we show how these affect the evolution of cooperation in social dilemmas. We consider first-order, second-order, as well as higher-order models in well-mixed and structured populations, and we review experimental works that support and inform the results of mathematical modeling and simulations. We also provide a synthesis of the reviewed researches along with an outlook in terms of six directions that seem particularly promising to explore in the future.
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Affiliation(s)
- Chengyi Xia
- School of Artificial Intelligence, Tiangong University, Tianjin 300384, China
| | - Juan Wang
- School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China.
| | - Matjaž Perc
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404332, Taiwan; Alma Mater Europaea, Slovenska ulica 17, 2000 Maribor, Slovenia; Complexity Science Hub Vienna, Josefstädterstraße 39, 1080 Vienna, Austria
| | - Zhen Wang
- Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xian 710072, China.
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10
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Kates-Harbeck J, Nowak M. Trust based attachment. PLoS One 2023; 18:e0288142. [PMID: 37610996 PMCID: PMC10446209 DOI: 10.1371/journal.pone.0288142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 06/20/2023] [Indexed: 08/25/2023] Open
Abstract
In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions [1-13]. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem [14]. To quantify this notion, we calculate the expected number of individuals, the "audience", who find out about a particular interaction. For a potential donor, a larger audience constitutes higher reputational stakes, and thus a higher incentive, to perform "good" actions in line with current social norms [7, 15]. For a receiver, a larger audience therefore increases the trust that the partner will be cooperative. This idea can be used for an algorithm that generates social networks, which we call trust based attachment (TBA). TBA produces graphs that share crucial quantitative properties with real-world networks, such as high clustering, small-world behavior, and powerlaw degree distributions [16-21]. We also show that TBA can be approximated by simple friend-of-friend routines based on triadic closure, which are known to be highly effective at generating realistic social network structures [19, 22-25]. Therefore, our work provides a new justification for triadic closure in social contexts based on notions of trust, gossip, and social information spread. These factors are thus identified as potential significant influences on how humans form social ties.
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Affiliation(s)
- Julian Kates-Harbeck
- Department of Physics, Harvard University, Cambridge, MA, United States of America
| | - Martin Nowak
- Department of Mathematics, Harvard University, Cambridge, MA, United States of America
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, United States of America
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11
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Murase Y, Hilbe C. Indirect reciprocity with stochastic and dual reputation updates. PLoS Comput Biol 2023; 19:e1011271. [PMID: 37471286 PMCID: PMC10359017 DOI: 10.1371/journal.pcbi.1011271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/13/2023] [Indexed: 07/22/2023] Open
Abstract
Cooperation is a crucial aspect of social life, yet understanding the nature of cooperation and how it can be promoted is an ongoing challenge. One mechanism for cooperation is indirect reciprocity. According to this mechanism, individuals cooperate to maintain a good reputation. This idea is embodied in a set of social norms called the "leading eight". When all information is publicly available, these norms have two major properties. Populations that employ these norms are fully cooperative, and they are stable against invasion by alternative norms. In this paper, we extend the framework of the leading eight in two directions. First, we include norms with 'dual' reputation updates. These norms do not only assign new reputations to an acting donor; they also allow to update the reputation of the passive recipient. Second, we allow social norms to be stochastic. Such norms allow individuals to evaluate others with certain probabilities. Using this framework, we characterize all evolutionarily stable norms that lead to full cooperation in the public information regime. When only the donor's reputation is updated, and all updates are deterministic, we recover the conventional model. In that case, we find two classes of stable norms: the leading eight and the 'secondary sixteen'. Stochasticity can further help to stabilize cooperation when the benefit of cooperation is comparably small. Moreover, updating the recipients' reputations can help populations to recover more quickly from errors. Overall, our study highlights a remarkable trade-off between the evolutionary stability of a norm and its robustness with respect to errors. Norms that correct errors quickly require higher benefits of cooperation to be stable.
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Affiliation(s)
- Yohsuke Murase
- RIKEN Center for Computational Science, Kobe, Japan
- Max Planck Research Group 'Dynamics of Social Behavior', Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Christian Hilbe
- Max Planck Research Group 'Dynamics of Social Behavior', Max Planck Institute for Evolutionary Biology, Plön, Germany
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12
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Inaba M, Akiyama E. Evolution of cooperation in multiplex networks through asymmetry between interaction and replacement. Sci Rep 2023; 13:9814. [PMID: 37330611 PMCID: PMC10276876 DOI: 10.1038/s41598-023-37074-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/15/2023] [Indexed: 06/19/2023] Open
Abstract
Cooperation is the foundation of society and has been the subject of numerous studies over the past three decades. However, the mechanisms underlying the spread of cooperation within a group are not yet fully comprehended. We analyze cooperation in multiplex networks, a model that has recently gained attention for successfully capturing certain aspects of human social connections. Previous studies on the evolution of cooperation in multiplex networks have shown that cooperative behavior is promoted when the two key processes in evolution, interaction and strategy replacement, are performed with the same partner as much as possible, that is, symmetrically, in a variety of network structures. We focus on a particular type of symmetry, namely, symmetry in the scope of communication, to investigate whether cooperation is promoted or hindered when interactions and strategy replacements have different scopes. Through multiagent simulations, we found some cases where asymmetry can promote cooperation, contrasting with previous studies. These results hint toward the potential effectiveness of not only symmetrical but also asymmetrical approaches in fostering cooperation within particular groups under certain social conditions.
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Affiliation(s)
- Masaaki Inaba
- Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan.
| | - Eizo Akiyama
- Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan
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13
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Kessinger TA, Tarnita CE, Plotkin JB. Evolution of norms for judging social behavior. Proc Natl Acad Sci U S A 2023; 120:e2219480120. [PMID: 37276388 PMCID: PMC10268218 DOI: 10.1073/pnas.2219480120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 05/03/2023] [Indexed: 06/07/2023] Open
Abstract
Reputations provide a powerful mechanism to sustain cooperation, as individuals cooperate with those of good social standing. But how should someone's reputation be updated as we observe their social behavior, and when will a population converge on a shared norm for judging behavior? Here, we develop a mathematical model of cooperation conditioned on reputations, for a population that is stratified into groups. Each group may subscribe to a different social norm for assessing reputations and so norms compete as individuals choose to move from one group to another. We show that a group initially comprising a minority of the population may nonetheless overtake the entire population-especially if it adopts the Stern Judging norm, which assigns a bad reputation to individuals who cooperate with those of bad standing. When individuals do not change group membership, stratifying reputation information into groups tends to destabilize cooperation, unless individuals are strongly insular and favor in-group social interactions. We discuss the implications of our results for the structure of information flow in a population and for the evolution of social norms of judgment.
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Affiliation(s)
| | - Corina E. Tarnita
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ08544
| | - Joshua B. Plotkin
- Department of Biology, University of Pennsylvania, Philadelphia, PA19104
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA19104
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14
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Kabir KA. Impact of human cooperation on vaccination behaviors. Heliyon 2023; 9:e16748. [PMID: 37292270 PMCID: PMC10245234 DOI: 10.1016/j.heliyon.2023.e16748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 06/10/2023] Open
Abstract
This paper studies a dynamic vaccination game model embedded with vaccine cost-effectiveness and dyadic game during an epidemic, assuming the appearance of cooperation among individuals from an evolutionary perspective. The infection dynamics of the individuals' states follow a modified S/VIS (susceptible/vaccinated-infected-susceptible) dynamics. Initially, we assume that the individuals are unsure about their infection status. Thus, they make decisions regarding their options based on their neighbors' perceptions, the prevalence of the disease, and the characteristics of the available vaccines. We then consider the strategy updating process IBRA (individuals-based risk assessment) concerning an individual's committing vaccination based on a neighbor's decision. In the perspective of social dilemma, it presents the idea of social efficiency deficit to find the gap between social optimum and Nash equilibrium point based on dilemma strength by considering vaccine decision. The cost and cooperative behavior depend on disease severity, neighbor's attitude, and vaccine properties to obtain a reduced-order optimal solution to control infectious diseases. Vaccine factors (efficiency, cost, and benefit) are crucial in changing human vaccine decisions and cooperative behavior. It turns out that, even in the prisoner's dilemma case, where all defection attitude occurs, vaccine uptake (cooperation) increases. Finally, extensive numerical studies were presented that illustrate interesting phenomena and investigate the ultimate extent of the epidemic, vaccination coverage, average social benefits, and the social efficiency deficit concerning optimal strategies and the dynamic vaccine attitudes of individuals. PACS numbers. Theory and modeling; computer simulation, 87.15. Aa; Dynamics of evolution, 87.23. Kg.
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15
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Fujimoto Y, Ohtsuki H. Evolutionary stability of cooperation in indirect reciprocity under noisy and private assessment. Proc Natl Acad Sci U S A 2023; 120:e2300544120. [PMID: 37155910 PMCID: PMC10194006 DOI: 10.1073/pnas.2300544120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/09/2023] [Indexed: 05/10/2023] Open
Abstract
Indirect reciprocity is a mechanism that explains large-scale cooperation in humans. In indirect reciprocity, individuals use reputations to choose whether or not to cooperate with a partner and update others' reputations. A major question is how the rules to choose their actions and the rules to update reputations evolve. In the public reputation case where all individuals share the evaluation of others, social norms called Simple Standing (SS) and Stern Judging (SJ) have been known to maintain cooperation. However, in the case of private assessment where individuals independently evaluate others, the mechanism of maintenance of cooperation is still largely unknown. This study theoretically shows for the first time that cooperation by indirect reciprocity can be evolutionarily stable under private assessment. Specifically, we find that SS can be stable, but SJ can never be. This is intuitive because SS can correct interpersonal discrepancies in reputations through its simplicity. On the other hand, SJ is too complicated to avoid an accumulation of errors, which leads to the collapse of cooperation. We conclude that moderate simplicity is a key to stable cooperation under the private assessment. Our result provides a theoretical basis for the evolution of human cooperation.
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Affiliation(s)
- Yuma Fujimoto
- Research Center for Integrative Evolutionary Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama240-0193, Japan
- Universal Biology Institute, The University of Tokyo, Bunkyo-ku113-0033, Japan
- CyberAgent, Inc., Shibuya-ku150-0042, Japan
| | - Hisashi Ohtsuki
- Research Center for Integrative Evolutionary Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama240-0193, Japan
- Department of Evolutionary Studies of Biosystems, SOKENDAI, Hayama240-0193, Japan
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16
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Schmid L, Ekbatani F, Hilbe C, Chatterjee K. Quantitative assessment can stabilize indirect reciprocity under imperfect information. Nat Commun 2023; 14:2086. [PMID: 37045828 PMCID: PMC10097696 DOI: 10.1038/s41467-023-37817-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 03/24/2023] [Indexed: 04/14/2023] Open
Abstract
The field of indirect reciprocity investigates how social norms can foster cooperation when individuals continuously monitor and assess each other's social interactions. By adhering to certain social norms, cooperating individuals can improve their reputation and, in turn, receive benefits from others. Eight social norms, known as the "leading eight," have been shown to effectively promote the evolution of cooperation as long as information is public and reliable. These norms categorize group members as either 'good' or 'bad'. In this study, we examine a scenario where individuals instead assign nuanced reputation scores to each other, and only cooperate with those whose reputation exceeds a certain threshold. We find both analytically and through simulations that such quantitative assessments are error-correcting, thus facilitating cooperation in situations where information is private and unreliable. Moreover, our results identify four specific norms that are robust to such conditions, and may be relevant for helping to sustain cooperation in natural populations.
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Affiliation(s)
- Laura Schmid
- KAIST Graduate School of AI, 02455, Seoul, South Korea.
| | - Farbod Ekbatani
- Booth School of Business, The University of Chicago, Chicago, IL, 60637, USA
| | - Christian Hilbe
- Max Planck Research Group Dynamics of Social Behavior, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany
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17
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Hu K, Wang P, He J, Perc M, Shi L. Complex evolutionary interactions in multiple populations. Phys Rev E 2023; 107:044301. [PMID: 37198848 DOI: 10.1103/physreve.107.044301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 03/22/2023] [Indexed: 05/19/2023]
Abstract
In competitive settings that entail several populations, individuals often engage in intra- and interpopulation interactions that determine their fitness and evolutionary success. With this simple motivation, we here study a multipopulation model where individuals engage in group interactions within their own population and in pairwise interactions with individuals from different populations. We use the evolutionary public goods game and the prisoner's dilemma game to describe these group and pairwise interactions, respectively. We also take into account asymmetry in the extent to which group and pairwise interactions determine the fitness of individuals. We find that interactions across multiple populations reveal new mechanisms through which the evolution of cooperation can be promoted, but this depends on the level of interaction asymmetry. If inter- and intrapopulation interactions are symmetric, the sole presence of multiple populations promotes the evolution of cooperation. Asymmetry in the interactions can further promote cooperation at the expense of the coexistence of the competing strategies. An in-depth analysis of the spatiotemporal dynamics reveals loop-dominated structures and pattern formation that can explain the various evolutionary outcomes. Thus, complex evolutionary interactions in multiple populations reveal an intricate interplay between cooperation and coexistence, and they also open up the path toward further explorations of multipopulation games and biodiversity.
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Affiliation(s)
- Kaipeng Hu
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Pengyue Wang
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Junzhou He
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Matjaž Perc
- Faculty of Natural Sciences and Mathematics, University of Maribor, 2000 Maribor, Slovenia
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 404332, Taiwan
- Alma Mater Europaea, 2000 Maribor, Slovenia
- Complexity Science Hub Vienna, 1080 Vienna, Austria
- Department of Physics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, Republic of Korea
| | - Lei Shi
- School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China
- Interdisciplinary Research Institute of Data Science, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China
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18
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Dong L, Ji T, Zhang J. Motivational Understanding of MOOC Learning: The Impacts of Technology Fit and Subjective Norms. Behav Sci (Basel) 2023; 13:bs13020098. [PMID: 36829327 PMCID: PMC9952167 DOI: 10.3390/bs13020098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 01/17/2023] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
This study examines the mechanisms underlying the relationship between motivation and massive open online course (MOOC) learning intention, and the contextual moderators that affect this mechanism. Drawing on motivational theory and the related literature, this study investigates how motivation affects students' intention to learn with MOOCs and the related meditation and moderation effects. The findings of our study show that both extrinsic and intrinsic motivations have a significant influence on intention to learn with MOOCs. In addition, the results also suggest that the relationship between extrinsic motivation and intention to learn is mediated by the technology fit perceived by learners but not the relationship between intrinsic motivation and intention to learn. Furthermore, the relationships between both extrinsic and intrinsic motivation and intention to learn are moderated by subjective norms. This study enriches the extant literature on the impact of technology fit and subjective norms on MOOC learning. Few studies have focused on how students can be effectively encouraged to take MOOCs. Given the lack of theoretical and empirical research, this study developed a theoretical model and conducted an empirical study to fill the research gap.
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Affiliation(s)
- Lingfeng Dong
- Alibaba Business College, Hangzhou Normal University, Hangzhou 311121, China
| | - Ting Ji
- School of Management, Zhejiang University, Hangzhou 310058, China
| | - Jie Zhang
- School of Business, Hangzhou City University, Hangzhou 310015, China
- Correspondence:
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19
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Li Q, Li S, Zhang Y, Chen X, Yang S. Social norms of fairness with reputation-based role assignment in the dictator game. CHAOS (WOODBURY, N.Y.) 2022; 32:113117. [PMID: 36456315 DOI: 10.1063/5.0109451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
A vast body of experiments share the view that social norms are major factors for the emergence of fairness in a population of individuals playing the dictator game (DG). Recently, to explore which social norms are conducive to sustaining cooperation has obtained considerable concern. However, thus, far few studies have investigated how social norms influence the evolution of fairness by means of indirect reciprocity. In this study, we propose an indirect reciprocal model of the DG and consider that an individual can be assigned as the dictator due to its good reputation. We investigate the "leading eight" norms and all second-order social norms by a two-timescale theoretical analysis. We show that when role assignment is based on reputation, four of the "leading eight" norms, including stern judging and simple standing, lead to a high level of fairness, which increases with the selection intensity. Our work also reveals that not only the correct treatment of making a fair split with good recipients but also distinguishing unjustified unfair split from justified unfair split matters in elevating the level of fairness.
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Affiliation(s)
- Qing Li
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Songtao Li
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Yanling Zhang
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Xiaojie Chen
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Shuo Yang
- Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
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20
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Otten K, Frey UJ, Buskens V, Przepiorka W, Ellemers N. Human cooperation in changing groups in a large-scale public goods game. Nat Commun 2022; 13:6399. [PMID: 36302777 PMCID: PMC9613774 DOI: 10.1038/s41467-022-34160-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 10/17/2022] [Indexed: 12/25/2022] Open
Abstract
How people cooperate to provide public goods is an important scientific question and relates to many societal problems. Previous research studied how people cooperate in stable groups in repeated or one-time-only encounters. However, most real-world public good problems occur in groups with a gradually changing composition due to old members leaving and new members arriving. How group changes are related to cooperation in public good provision is not well understood. To address this issue, we analyze a dataset from an online public goods game comprising approximately 1.5 million contribution decisions made by about 135 thousand players in about 11.3 thousand groups with about 234 thousand changes in group composition. We find that changes in group composition negatively relate to cooperation. Our results suggest that this is related to individuals contributing less in the role of newcomers than in the role of incumbents. During the process of moving from newcomer status to incumbent status, individuals cooperate more and more in line with incumbents.
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Affiliation(s)
- Kasper Otten
- grid.5477.10000000120346234Utrecht University, Department of Sociology/ICS, Utrecht, the Netherlands
| | - Ulrich J. Frey
- grid.8664.c0000 0001 2165 8627Justus-Liebig-University Giessen, Faculty of Biology and Chemistry, Giessen, Germany
| | - Vincent Buskens
- grid.5477.10000000120346234Utrecht University, Department of Sociology/ICS, Utrecht, the Netherlands
| | - Wojtek Przepiorka
- grid.5477.10000000120346234Utrecht University, Department of Sociology/ICS, Utrecht, the Netherlands
| | - Naomi Ellemers
- grid.5477.10000000120346234Utrecht University, Department of Psychology, Utrecht, the Netherlands
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21
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Livan G, Pappalardo G, Mantegna RN. Quantifying the relationship between specialisation and reputation in an online platform. Sci Rep 2022; 12:16699. [PMID: 36202960 PMCID: PMC9537143 DOI: 10.1038/s41598-022-20767-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/19/2022] [Indexed: 11/08/2022] Open
Abstract
Online platforms implement digital reputation systems in order to steer individual user behaviour towards outcomes that are deemed desirable on a collective level. At the same time, most online platforms are highly decentralised environments, leaving their users plenty of room to pursue different strategies and diversify behaviour. We provide a statistical characterisation of the user behaviour emerging from the interplay of such competing forces in Stack Overflow, a long-standing knowledge sharing platform. Over the 11 years covered by our analysis, we represent the interactions between users and topics as bipartite networks. We find such networks to display nested structures akin to those observed in ecological systems, demonstrating that the platform's user base consistently self-organises into specialists and generalists, i.e., users who focus on narrow and broad sets of topics, respectively. We relate the emergence of these behaviours to the platform's reputation system with a series of data-driven models, and find specialisation to be statistically associated with a higher ability to post the best answers to a question. We contrast our findings with observations made in top-down environments-such as firms and corporations-where generalist skills are consistently found to be more successful.
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Affiliation(s)
- Giacomo Livan
- Department of Computer Science, University College London, Gower Street, London, WC1E 6EA, UK.
- Systemic Risk Centre, London School of Economics and Political Sciences, Houghton Street, London, WC2A 2AE, UK.
| | - Giuseppe Pappalardo
- Dipartimento di Fisica 'Ettore Majorana', Università di Catania, Via S. Sofia, 64, 95123, Catania, Italy
| | - Rosario N Mantegna
- Dipartimento di Fisica e Chimica Emilio Segrè, Università di Palermo, Viale delle Science, Ed. 18, 90128, Palermo, Italy
- Complexity Science Hub Vienna, Josefstädter Strasse 39, 1080, Vienna, Austria
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22
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Salahshour M. Interaction between games give rise to the evolution of moral norms of cooperation. PLoS Comput Biol 2022; 18:e1010429. [PMID: 36173936 PMCID: PMC9521931 DOI: 10.1371/journal.pcbi.1010429] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/21/2022] [Indexed: 11/18/2022] Open
Abstract
In many biological populations, such as human groups, individuals face a complex strategic setting, where they need to make strategic decisions over a diverse set of issues and their behavior in one strategic context can affect their decisions in another. This raises the question of how the interaction between different strategic contexts affects individuals’ strategic choices and social norms? To address this question, I introduce a framework where individuals play two games with different structures and decide upon their strategy in a second game based on their knowledge of their opponent’s strategy in the first game. I consider both multistage games, where the same opponents play the two games consecutively, and reputation-based model, where individuals play their two games with different opponents but receive information about their opponent’s strategy. By considering a case where the first game is a social dilemma, I show that when the second game is a coordination or anti-coordination game, the Nash equilibrium of the coupled game can be decomposed into two classes, a defective equilibrium which is composed of two simple equilibrium of the two games, and a cooperative equilibrium, in which coupling between the two games emerge and sustain cooperation in the social dilemma. For the existence of the cooperative equilibrium, the cost of cooperation should be smaller than a value determined by the structure of the second game. Investigation of the evolutionary dynamics shows that a cooperative fixed point exists when the second game belongs to coordination or anti-coordination class in a mixed population. However, the basin of attraction of the cooperative fixed point is much smaller for the coordination class, and this fixed point disappears in a structured population. When the second game belongs to the anti-coordination class, the system possesses a spontaneous symmetry-breaking phase transition above which the symmetry between cooperation and defection breaks. A set of cooperation supporting moral norms emerges according to which cooperation stands out as a valuable trait. Notably, the moral system also brings a more efficient allocation of resources in the second game. This observation suggests a moral system has two different roles: Promotion of cooperation, which is against individuals’ self-interest but beneficial for the population, and promotion of organization and order, which is at both the population’s and the individual’s self-interest. Interestingly, the latter acts like a Trojan horse: Once established out of individuals’ self-interest, it brings the former with itself. Importantly, the fact that the evolution of moral norms depends only on the cost of cooperation and is independent of the benefit of cooperation implies that moral norms can be harmful and incur a pure collective cost, yet they are just as effective in promoting order and organization. Finally, the model predicts that recognition noise can have a surprisingly positive effect on the evolution of moral norms and facilitates cooperation in the Snow Drift game in structured populations. How do moral norms spontaneously evolve in the presence of selfish incentives? An answer to this question is provided by the observation that moral systems have two distinct functions: Besides encouraging self-sacrificing cooperation, they also bring organization and order into the societies. In contrast to the former, which is costly for the individuals but beneficial for the group, the latter is beneficial for both the group and the individuals. A simple evolutionary model suggests this latter aspect is what makes a moral system evolve based on the individuals’ self-interest. However, a moral system behaves like a Trojan horse: Once established out of the individuals’ self-interest to promote order and organization, it also brings self-sacrificing cooperation.
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Affiliation(s)
- Mohammad Salahshour
- Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
- Max Planck Institute of Animal Behavior, Radolfzell, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
- * E-mail:
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23
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McAvoy A, Kates-Harbeck J, Chatterjee K, Hilbe C. Evolutionary instability of selfish learning in repeated games. PNAS NEXUS 2022; 1:pgac141. [PMID: 36714856 PMCID: PMC9802390 DOI: 10.1093/pnasnexus/pgac141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 07/22/2022] [Indexed: 02/01/2023]
Abstract
Across many domains of interaction, both natural and artificial, individuals use past experience to shape future behaviors. The results of such learning processes depend on what individuals wish to maximize. A natural objective is one's own success. However, when two such "selfish" learners interact with each other, the outcome can be detrimental to both, especially when there are conflicts of interest. Here, we explore how a learner can align incentives with a selfish opponent. Moreover, we consider the dynamics that arise when learning rules themselves are subject to evolutionary pressure. By combining extensive simulations and analytical techniques, we demonstrate that selfish learning is unstable in most classical two-player repeated games. If evolution operates on the level of long-run payoffs, selection instead favors learning rules that incorporate social (other-regarding) preferences. To further corroborate these results, we analyze data from a repeated prisoner's dilemma experiment. We find that selfish learning is insufficient to explain human behavior when there is a trade-off between payoff maximization and fairness.
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Affiliation(s)
| | | | | | - Christian Hilbe
- Max Planck Research Group: Dynamics of Social Behavior, Max Planck Institute for Evolutionary Biology, Plön, Germany
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24
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Fujimoto Y, Ohtsuki H. Reputation structure in indirect reciprocity under noisy and private assessment. Sci Rep 2022; 12:10500. [PMID: 35732644 PMCID: PMC9217807 DOI: 10.1038/s41598-022-14171-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/02/2022] [Indexed: 12/04/2022] Open
Abstract
Evaluation relationships are pivotal for maintaining a cooperative society. A formation of the evaluation relationships has been discussed in terms of indirect reciprocity, by modeling dynamics of good or bad reputations among individuals. Recently, a situation that individuals independently evaluate others with errors (i.e., noisy and private reputation) is considered, where the reputation structure (from what proportion of individuals in the population each receives good reputations, defined as goodness here) becomes complex, and thus has been studied mainly with numerical simulations. The present study gives a theoretical analysis of such complex reputation structure. We formulate the time change of goodness of individuals caused by updates of reputations among individuals. By considering a large population, we derive dynamics of the frequency distribution of goodnesses. An equilibrium state of the dynamics is approximated by a summation of Gaussian functions. We demonstrate that the theoretical solution well fits the numerical calculation. From the theoretical solution, we obtain a new interpretation of the complex reputation structure. This study provides a novel mathematical basis for cutting-edge studies on indirect reciprocity.
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Affiliation(s)
- Yuma Fujimoto
- Department of Evolutionary Studies of Biosystems, SOKENDAI, Shonan Village, Hayama, Kanagawa, 240-0193, Japan.
- Universal Biology Institute (UBI), The University of Tokyo, 7-3-1 Hongo, Tokyo, Bunkyo-ku, 113-0033, Japan.
| | - Hisashi Ohtsuki
- Department of Evolutionary Studies of Biosystems, SOKENDAI, Shonan Village, Hayama, Kanagawa, 240-0193, Japan
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25
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Jamroga W, Kurpiewski D, Malvone V. How to measure usable security: Natural strategies in voting protocols. JOURNAL OF COMPUTER SECURITY 2022. [DOI: 10.3233/jcs-210049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Formal analysis of security is often focused on the technological side of the system. One implicitly assumes that the users will behave in the right way to preserve the relevant security properties. In real life, this cannot be taken for granted. In particular, security mechanisms that are difficult and costly to use are often ignored by the users, and do not really defend the system against possible attacks. Here, we propose a graded notion of security based on the complexity of the user’s strategic behavior. More precisely, we suggest that the level to which a security property φ is satisfied can be defined in terms of: (a) the complexity of the strategy that the user needs to execute to make φ true, and (b) the resources that the user must employ on the way. The simpler and cheaper to obtain φ, the higher the degree of security. We demonstrate how the idea works in a case study based on an electronic voting scenario. To this end, we model the vVote implementation of the Prêt à Voter voting protocol for coercion-resistant and voter-verifiable elections. Then, we identify “natural” strategies for the voter to obtain voter-verifiability, and measure the voter’s effort that they require. We also consider the dual view of graded security, measured by the complexity of the attacker’s strategy to compromise the relevant properties of the election.
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Affiliation(s)
- Wojciech Jamroga
- Interdisc. Centre on Security, Reliability and Trust, SnT, University of Luxembourg
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
| | - Damian Kurpiewski
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
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26
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Zhang L, Zhang L, Huang C. Defectors in bad circumstances possessing higher reputation can promote cooperation. CHAOS (WOODBURY, N.Y.) 2022; 32:043114. [PMID: 35489841 DOI: 10.1063/5.0084901] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/22/2022] [Indexed: 06/14/2023]
Abstract
In nature and human society, social relationships and behavior patterns are usually unpredictable. In any interaction, individuals will constantly have to deal with prior uncertainty. The concept of "reputation" can provide some information to mitigate such uncertainty. In previous studies, researchers have considered that only cooperators are able to maintain a high reputation; no matter the circumstances of a defector, they are classified as a faithless individual. In reality, however, some individuals will be forced to defect to protect themselves against exploitation. Therefore, it makes sense that defectors in bad circumstances could also obtain higher reputations, and cooperators can maintain higher reputations in comfortable circumstances. In this work, the reputations of individuals are calculated using the fraction of their neighbors who have the same strategy. In this way, some defectors in a population may obtain higher reputations than some cooperators. We introduce this reputation rule using heterogeneous investments in public goods games. Our numerical simulation results indicate that this reputation rule and heterogeneous investments can better stimulate cooperation. Additionally, stronger investment heterogeneity can further increase the level of cooperation. To explain this phenomenon, dynamical evolution is observed in Monte Carlo simulations. We also investigated the effects of the noise intensity of the irrational population and the original proportion of cooperation in the population. The robustness of this cooperation model was also considered with respect to the network structure and total investment, and we found that the conclusions remained the same.
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Affiliation(s)
- Lan Zhang
- School of Information, Xi'an University of Finance and Economics, Xi'an 710100, China
| | - Liming Zhang
- School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Changwei Huang
- School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China
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27
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Abstract
'Personal responsibility', one of the basic principles of social governance, requires one to be accountable for what one does. However, personal responsibility is far from the only norm ruling human interactions, especially in social and economic activities. In many collective communities such as among enterprise colleagues and family members, one's personal interests are often bound to others'-once one member breaks the rule, a group of people have to bear the punishment or sanction. Such a mechanism is termed 'joint liability'. Although many real-world cases have evidenced that joint liability can help to maintain collective collaboration, a deep and systematic theoretical analysis on how and when it promotes cooperation remains lacking. Here, we use evolutionary game theory to model an interacting system with joint liability, where one's losing credit could deteriorate the reputation of the whole group. We provide the analytical condition to predict when cooperation evolves and analytically prove that in the presence of punishment, being jointly liable greatly promotes cooperation. Our work stresses that joint liability is of great significance in promoting current economic prosperity.
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Affiliation(s)
- Guocheng Wang
- Center for Systems and Control, College of Engineering, Peking University, Beijing 100871, People's Republic of China
| | - Qi Su
- Center for Mathematical Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Mathematics, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Long Wang
- Center for Systems and Control, College of Engineering, Peking University, Beijing 100871, People's Republic of China.,Center for Multi-Agent Research, Institute for Artificial Intelligence, Peking University, Beijing 100871, People's Republic of China
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28
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Liu L, Xiao Z, Chen X, Szolnoki A. Early exclusion leads to cyclical cooperation in repeated group interactions. J R Soc Interface 2022; 19:20210755. [PMID: 35317651 PMCID: PMC8941418 DOI: 10.1098/rsif.2021.0755] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Explaining the emergence and maintenance of cooperation among selfish individuals from an evolutionary perspective remains a grand challenge in biology, economy and social sciences. Social exclusion is believed to be an answer to this conundrum. However, previously related studies often assume one-shot interactions and ignore how free-riding is identified, which seem to be too idealistic. In this work, we consider repeated interactions where excluders need to pay a monitoring cost to identify free-riders for exclusion and free-riders cannot participate in the following possible game interactions once they are identified and excluded by excluders in the repeated interaction process. We reveal that the introduction of such exclusion can prevent the breakdown of cooperation in repeated group interactions. In particular, we demonstrate that an evolutionary oscillation among cooperators, defectors and excluders can appear in infinitely large populations when early exclusion is implemented. In addition, we find that the population spends most of the time in states where cooperators dominate for early exclusion when stochastic mutation-selection is considered in finite populations. Our results highlight that early exclusion is successful in solving the mentioned enigma of cooperation in repeated group interactions.
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Affiliation(s)
- Linjie Liu
- College of Science, Northwest A & F University, Yangling 712100, People’s Republic of China
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
| | - Zhilong Xiao
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
| | - Xiaojie Chen
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
| | - Attila Szolnoki
- Institute of Technical Physics and Materials Science, Centre for Energy Research, PO Box 49, Budapest 1525, Hungary
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29
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Giardini F, Balliet D, Power EA, Számadó S, Takács K. Four Puzzles of Reputation-Based Cooperation : Content, Process, Honesty, and Structure. HUMAN NATURE (HAWTHORNE, N.Y.) 2022; 33:43-61. [PMID: 34961914 PMCID: PMC8964644 DOI: 10.1007/s12110-021-09419-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Accepted: 11/13/2021] [Indexed: 11/22/2022]
Abstract
Research in various disciplines has highlighted that humans are uniquely able to solve the problem of cooperation through the informal mechanisms of reputation and gossip. Reputation coordinates the evaluative judgments of individuals about one another. Direct observation of actions and communication are the essential routes that are used to establish and update reputations. In large groups, where opportunities for direct observation are limited, gossip becomes an important channel to share individual perceptions and evaluations of others that can be used to condition cooperative action. Although reputation and gossip might consequently support large-scale human cooperation, four puzzles need to be resolved to understand the operation of reputation-based mechanisms. First, we need empirical evidence of the processes and content that form reputations and how this may vary cross-culturally. Second, we lack an understanding of how reputation is determined from the muddle of imperfect, biased inputs people receive. Third, coordination between individuals is only possible if reputation sharing and signaling is to a large extent reliable and valid. Communication, however, is not necessarily honest and reliable, so theoretical and empirical work is needed to understand how gossip and reputation can effectively promote cooperation despite the circulation of dishonest gossip. Fourth, reputation is not constructed in a social vacuum; hence we need a better understanding of the way in which the structure of interactions affects the efficiency of gossip for establishing reputations and fostering cooperation.
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Affiliation(s)
- Francesca Giardini
- Department of Sociology, University of Groningen, Grote Rozenstraat, 31 - 9712 TG Groningen, Netherlands
| | - Daniel Balliet
- Department of Experimental and Applied Social Psychology, VU Amsterdam, Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - Eleanor A. Power
- London School of Economics and Political Science, Department of Methodology, Houghton Street, WC2A 2AE London, UK
| | - Szabolcs Számadó
- Department of Sociology and Communication, Budapest University of Technology and Economics, Egry J. u. 1. Floor 7, 1111 Budapest, Hungary
- Centre for Social Sciences, CSS-RECENS, Tóth Kálmán u. 4, 1097 Budapest, Hungary
| | - Károly Takács
- The Institute for Analytical Sociology, Linköping University, 601 74 Norrköping, Sweden
- Centre for Social Sciences, CSS-RECENS, Tóth Kálmán u. 4, 1097 Budapest, Hungary
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30
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Murase Y, Kim M, Baek SK. Social norms in indirect reciprocity with ternary reputations. Sci Rep 2022; 12:455. [PMID: 35013393 PMCID: PMC8748885 DOI: 10.1038/s41598-021-04033-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/07/2021] [Indexed: 11/23/2022] Open
Abstract
Indirect reciprocity is a key mechanism that promotes cooperation in social dilemmas by means of reputation. Although it has been a common practice to represent reputations by binary values, either ‘good’ or ‘bad’, such a dichotomy is a crude approximation considering the complexity of reality. In this work, we studied norms with three different reputations, i.e., ‘good’, ‘neutral’, and ‘bad’. Through massive supercomputing for handling more than thirty billion possibilities, we fully identified which norms achieve cooperation and possess evolutionary stability against behavioural mutants. By systematically categorizing all these norms according to their behaviours, we found similarities and dissimilarities to their binary-reputation counterpart, the leading eight. We obtained four rules that should be satisfied by the successful norms, and the behaviour of the leading eight can be understood as a special case of these rules. A couple of norms that show counter-intuitive behaviours are also presented. We believe the findings are also useful for designing successful norms with more general reputation systems.
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Affiliation(s)
- Yohsuke Murase
- RIKEN Center for Computational Science, Kobe, Hyogo, 650-0047, Japan
| | - Minjae Kim
- Department of Physics, Pukyong National University, Busan, 48513, Korea
| | - Seung Ki Baek
- Department of Physics, Pukyong National University, Busan, 48513, Korea.
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31
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Link recommendation algorithms and dynamics of polarization in online social networks. Proc Natl Acad Sci U S A 2021; 118:2102141118. [PMID: 34876508 DOI: 10.1073/pnas.2102141118] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2021] [Indexed: 01/10/2023] Open
Abstract
The level of antagonism between political groups has risen in the past years. Supporters of a given party increasingly dislike members of the opposing group and avoid intergroup interactions, leading to homophilic social networks. While new connections offline are driven largely by human decisions, new connections on online social platforms are intermediated by link recommendation algorithms, e.g., "People you may know" or "Whom to follow" suggestions. The long-term impacts of link recommendation in polarization are unclear, particularly as exposure to opposing viewpoints has a dual effect: Connections with out-group members can lead to opinion convergence and prevent group polarization or further separate opinions. Here, we provide a complex adaptive-systems perspective on the effects of link recommendation algorithms. While several models justify polarization through rewiring based on opinion similarity, here we explain it through rewiring grounded in structural similarity-defined as similarity based on network properties. We observe that preferentially establishing links with structurally similar nodes (i.e., sharing many neighbors) results in network topologies that are amenable to opinion polarization. Hence, polarization occurs not because of a desire to shield oneself from disagreeable attitudes but, instead, due to the creation of inadvertent echo chambers. When networks are composed of nodes that react differently to out-group contacts, either converging or polarizing, we find that connecting structurally dissimilar nodes moderates opinions. Overall, our study sheds light on the impacts of social-network algorithms and unveils avenues to steer dynamics of radicalization and polarization in online social networks.
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32
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Perret C, Krellner M, Han TA. The evolution of moral rules in a model of indirect reciprocity with private assessment. Sci Rep 2021; 11:23581. [PMID: 34880264 PMCID: PMC8654852 DOI: 10.1038/s41598-021-02677-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/11/2021] [Indexed: 11/09/2022] Open
Abstract
Moral rules allow humans to cooperate by indirect reciprocity. Yet, it is not clear which moral rules best implement indirect reciprocity and are favoured by natural selection. Previous studies either considered only public assessment, where individuals are deemed good or bad by all others, or compared a subset of possible strategies. Here we fill this gap by identifying which rules are evolutionary stable strategies (ESS) among all possible moral rules while considering private assessment. We develop an analytical model describing the frequency of long-term cooperation, determining when a strategy can be invaded by another. We show that there are numerous ESSs in absence of errors, which however cease to exist when errors are present. We identify the underlying properties of cooperative ESSs. Overall, this paper provides a first exhaustive evolutionary invasion analysis of moral rules considering private assessment. Moreover, this model is extendable to incorporate higher-order rules and other processes.
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Affiliation(s)
- Cedric Perret
- Teesside University, Southfield Rd, Middlesbrough, TS1 3BX, UK.
| | - Marcus Krellner
- Teesside University, Southfield Rd, Middlesbrough, TS1 3BX, UK
| | - The Anh Han
- Teesside University, Southfield Rd, Middlesbrough, TS1 3BX, UK
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33
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Roberts G, Raihani N, Bshary R, Manrique HM, Farina A, Samu F, Barclay P. The benefits of being seen to help others: indirect reciprocity and reputation-based partner choice. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200290. [PMID: 34601903 PMCID: PMC8487748 DOI: 10.1098/rstb.2020.0290] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/13/2021] [Indexed: 01/06/2023] Open
Abstract
When one individual helps another, it benefits the recipient and may also gain a reputation for being cooperative. This may induce others to favour the helper in subsequent interactions, so investing in being seen to help others may be adaptive. The best-known mechanism for this is indirect reciprocity (IR), in which the profit comes from an observer who pays a cost to benefit the original helper. IR has attracted considerable theoretical and empirical interest, but it is not the only way in which cooperative reputations can bring benefits. Signalling theory proposes that paying a cost to benefit others is a strategic investment which benefits the signaller through changing receiver behaviour, in particular by being more likely to choose the signaller as a partner. This reputation-based partner choice can result in competitive helping whereby those who help are favoured as partners. These theories have been confused in the literature. We therefore set out the assumptions, the mechanisms and the predictions of each theory for how developing a cooperative reputation can be adaptive. The benefits of being seen to be cooperative may have been a major driver of sociality, especially in humans. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.
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Affiliation(s)
| | - Nichola Raihani
- Department of Experimental Psychology, University College London, London WC1H 0AP, UK
| | - Redouan Bshary
- Department of Biology, University of Neuchâtel, Neuchâtel 2009, Switzerland
| | - Héctor M. Manrique
- Department of Psicología y Sociología, Universidad de Zaragoza, Teruel, Teruel 44003, Spain
| | - Andrea Farina
- Leiden University, Leiden, Zuid-Holland, The Netherlands
| | - Flóra Samu
- Linköping University, Linköping, Östergötland, Sweden
| | - Pat Barclay
- Department of Psychology, University of Guelph, Guelph, Ontario, Canada N1G 2W1
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34
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Manrique HM, Zeidler H, Roberts G, Barclay P, Walker M, Samu F, Fariña A, Bshary R, Raihani N. The psychological foundations of reputation-based cooperation. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200287. [PMID: 34601920 PMCID: PMC8487732 DOI: 10.1098/rstb.2020.0287] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2021] [Indexed: 12/27/2022] Open
Abstract
Humans care about having a positive reputation, which may prompt them to help in scenarios where the return benefits are not obvious. Various game-theoretical models support the hypothesis that concern for reputation may stabilize cooperation beyond kin, pairs or small groups. However, such models are not explicit about the underlying psychological mechanisms that support reputation-based cooperation. These models therefore cannot account for the apparent rarity of reputation-based cooperation in other species. Here, we identify the cognitive mechanisms that may support reputation-based cooperation in the absence of language. We argue that a large working memory enhances the ability to delay gratification, to understand others' mental states (which allows for perspective-taking and attribution of intentions) and to create and follow norms, which are key building blocks for increasingly complex reputation-based cooperation. We review the existing evidence for the appearance of these processes during human ontogeny as well as their presence in non-human apes and other vertebrates. Based on this review, we predict that most non-human species are cognitively constrained to show only simple forms of reputation-based cooperation. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.
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Affiliation(s)
- Héctor M. Manrique
- Department of Psychology and Sociology, Universidad de Zaragoza, Campus Universitario de Teruel, Ciudad Escolar, s/n. 44003 Teruel, Spain
| | - Henriette Zeidler
- Department of Psychology, School of Life and Health Sciences, Aston University, Birmingham, UK
| | | | - Pat Barclay
- Psychology, University of Guelph, Guelph, Canada
| | - Michael Walker
- Department of Zoology and Physical Anthropology, Universidad de Murcia, Murcia, Spain
| | - Flóra Samu
- The Institute for Analytical Sociology, Linköping University, Linköping, Sweden
| | - Andrea Fariña
- Social, Economic, and Organizational Psychology, Leiden University, Leiden, The Netherlands
| | - Redouan Bshary
- Biology, University of Neuchâtel, Neuchâtel, Switzerland
| | - Nichola Raihani
- Experimental Psychology, University College London, London, UK
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35
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Takács K, Gross J, Testori M, Letina S, Kenny AR, Power EA, Wittek RPM. Networks of reliable reputations and cooperation: a review. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200297. [PMID: 34601917 PMCID: PMC8487750 DOI: 10.1098/rstb.2020.0297] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Reputation has been shown to provide an informal solution to the problem of cooperation in human societies. After reviewing models that connect reputations and cooperation, we address how reputation results from information exchange embedded in a social network that changes endogenously itself. Theoretical studies highlight that network topologies have different effects on the extent of cooperation, since they can foster or hinder the flow of reputational information. Subsequently, we review models and empirical studies that intend to grasp the coevolution of reputations, cooperation and social networks. We identify open questions in the literature concerning how networks affect the accuracy of reputations, the honesty of shared information and the spread of reputational information. Certain network topologies may facilitate biased beliefs and intergroup competition or in-group identity formation that could lead to high cooperation within but conflicts between different subgroups of a network. Our review covers theoretical, experimental and field studies across various disciplines that target these questions and could explain how the dynamics of interactions and reputations help or prevent the establishment and sustainability of cooperation in small- and large-scale societies. This article is part of the theme issue ‘The language of cooperation: reputation and honest signalling’.
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Affiliation(s)
- Károly Takács
- The Institute for Analytical Sociology, Linköping University, 601 74 Norrköping, Sweden.,Computational Social Science-Research Center for Educational and Network Studies (CSS-RECENS), Centre for Social Sciences, Tóth Kálmán u. 4., 1097 Budapest, Hungary
| | - Jörg Gross
- Institute of Psychology, Leiden University, Wassenaarseweg 52, 2333 AK, Leiden, The Netherlands
| | - Martina Testori
- Organization Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands
| | - Srebrenka Letina
- The Institute for Analytical Sociology, Linköping University, 601 74 Norrköping, Sweden.,Institute of Health and Wellbeing, MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Berkeley Square, 99 Berkeley Street, Glasgow G3 7HR, UK
| | - Adam R Kenny
- Institute of Cognitive and Evolutionary Anthropology, University of Oxford, 64 Banbury Road, Oxford OX2 6PN, UK.,Calleva Research Centre for Evolution and Human Sciences, Magdalen College, High Street, Oxford OX1 4AU, UK
| | - Eleanor A Power
- Department of Methodology, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK
| | - Rafael P M Wittek
- Department of Sociology, University of Groningen, Grote Rozenstraat 31, 9712 TG Groningen, The Netherlands
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36
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Santos FP, Pacheco JM, Santos FC. The complexity of human cooperation under indirect reciprocity. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200291. [PMID: 34601904 DOI: 10.1098/rstb.2020.0291] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Indirect reciprocity (IR) is a key mechanism to understand cooperation among unrelated individuals. It involves reputations and complex information processing, arising from social interactions. By helping someone, individuals may improve their reputation, which may be shared in a population and change the predisposition of others to reciprocate in the future. The reputation of individuals depends, in turn, on social norms that define a good or bad action, offering a computational and mathematical appealing way of studying the evolution of moral systems. Over the years, theoretical and empirical research has unveiled many features of cooperation under IR, exploring norms with varying degrees of complexity and information requirements. Recent results suggest that costly reputation spread, interaction observability and empathy are determinants of cooperation under IR. Importantly, such characteristics probably impact the level of complexity and information requirements for IR to sustain cooperation. In this review, we present and discuss those recent results. We provide a synthesis of theoretical models and discuss previous conclusions through the lens of evolutionary game theory and cognitive complexity. We highlight open questions and suggest future research in this domain. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.
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Affiliation(s)
- Fernando P Santos
- Informatics Institute, University of Amsterdam, Science Park 904, Amsterdam 1098XH, The Netherlands.,Department of Ecology and Evolutionary Biology, Princeton University, Princeton, USA.,ATP-Group, Porto Salvo P-2744-016, Portugal
| | - Jorge M Pacheco
- Centro de Biologia Molecular e Ambiental and Departamento de Matemática, Universidade do Minho, Braga 4710-057, Portugal.,ATP-Group, Porto Salvo P-2744-016, Portugal
| | - Francisco C Santos
- INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, Porto Salvo 2744-016, Portugal.,ATP-Group, Porto Salvo P-2744-016, Portugal
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37
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Számadó S, Balliet D, Giardini F, Power EA, Takács K. The language of cooperation: reputation and honest signalling. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200286. [PMID: 34601918 PMCID: PMC8487738 DOI: 10.1098/rstb.2020.0286] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2021] [Indexed: 11/12/2022] Open
Abstract
Large-scale non-kin cooperation is a unique ingredient of human success. This type of cooperation is challenging to explain in a world of self-interested individuals. There is overwhelming empirical evidence from different disciplines that reputation and gossip promote cooperation in humans in different contexts. Despite decades of research, important details of reputation systems are still unclear. Our goal with this theme issue is to promote an interdisciplinary approach that allows us to explore and understand the evolution and maintenance of reputation systems with a special emphasis on gossip and honest signalling. The theme issue is organized around four main questions: What are the necessary conditions for reputation-based systems? What is the content and context of reputation systems? How can reputations promote cooperation? And, what is the role of gossip in maintaining reputation systems and thus cooperation? This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.
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Affiliation(s)
- S. Számadó
- Department of Sociology and Communication, BUTE, Budapest, Hungary
- CSS-RECENS, Centre for Social Sciences, Budapest, Hungary
| | - D. Balliet
- Department of Experimental and Applied Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - F. Giardini
- Department of Sociology, University of Groningen, Groningen, The Netherlands
| | - E. A. Power
- Department of Methodology, London School of Economics and Political Science, London, UK
| | - K. Takács
- CSS-RECENS, Centre for Social Sciences, Budapest, Hungary
- Institute for Analytical Sociology, Linköping University, Linköping, Sweden
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38
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A unified framework of direct and indirect reciprocity. Nat Hum Behav 2021; 5:1292-1302. [PMID: 33986519 DOI: 10.1038/s41562-021-01114-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 04/12/2021] [Indexed: 02/03/2023]
Abstract
Direct and indirect reciprocity are key mechanisms for the evolution of cooperation. Direct reciprocity means that individuals use their own experience to decide whether to cooperate with another person. Indirect reciprocity means that they also consider the experiences of others. Although these two mechanisms are intertwined, they are typically studied in isolation. Here, we introduce a mathematical framework that allows us to explore both kinds of reciprocity simultaneously. We show that the well-known 'generous tit-for-tat' strategy of direct reciprocity has a natural analogue in indirect reciprocity, which we call 'generous scoring'. Using an equilibrium analysis, we characterize under which conditions either of the two strategies can maintain cooperation. With simulations, we additionally explore which kind of reciprocity evolves when members of a population engage in social learning to adapt to their environment. Our results draw unexpected connections between direct and indirect reciprocity while highlighting important differences regarding their evolvability.
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39
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Schmid L, Shati P, Hilbe C, Chatterjee K. The evolution of indirect reciprocity under action and assessment generosity. Sci Rep 2021; 11:17443. [PMID: 34465830 PMCID: PMC8408181 DOI: 10.1038/s41598-021-96932-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 08/17/2021] [Indexed: 11/08/2022] Open
Abstract
Indirect reciprocity is a mechanism for the evolution of cooperation based on social norms. This mechanism requires that individuals in a population observe and judge each other's behaviors. Individuals with a good reputation are more likely to receive help from others. Previous work suggests that indirect reciprocity is only effective when all relevant information is reliable and publicly available. Otherwise, individuals may disagree on how to assess others, even if they all apply the same social norm. Such disagreements can lead to a breakdown of cooperation. Here we explore whether the predominantly studied 'leading eight' social norms of indirect reciprocity can be made more robust by equipping them with an element of generosity. To this end, we distinguish between two kinds of generosity. According to assessment generosity, individuals occasionally assign a good reputation to group members who would usually be regarded as bad. According to action generosity, individuals occasionally cooperate with group members with whom they would usually defect. Using individual-based simulations, we show that the two kinds of generosity have a very different effect on the resulting reputation dynamics. Assessment generosity tends to add to the overall noise and allows defectors to invade. In contrast, a limited amount of action generosity can be beneficial in a few cases. However, even when action generosity is beneficial, the respective simulations do not result in full cooperation. Our results suggest that while generosity can favor cooperation when individuals use the most simple strategies of reciprocity, it is disadvantageous when individuals use more complex social norms.
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Affiliation(s)
- Laura Schmid
- IST Austria, Am Campus 1, 3400, Klosterneuburg, Austria.
| | - Pouya Shati
- Department of Computer Science, University of Toronto, Toronto, ON, M5S, Canada
| | - Christian Hilbe
- Max Planck Research Group Dynamics of Social Behavior, Max Planck Institute for Evolutionary Biology, 24306, Ploen, Germany
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40
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Local reputation, local selection, and the leading eight norms. Sci Rep 2021; 11:16560. [PMID: 34400674 PMCID: PMC8368190 DOI: 10.1038/s41598-021-95130-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 06/14/2021] [Indexed: 11/08/2022] Open
Abstract
Humans are capable of solving cooperation problems following social norms. Social norms dictate appropriate behaviour and judgement on others in response to their previous actions and reputation. Recently, the so-called leading eight norms have been identified from many potential social norms that can sustain cooperation through a reputation-based indirect reciprocity mechanism. Despite indirect reciprocity being claimed to extend direct reciprocity in larger populations where direct experiences cannot be accumulated, the success of social norms have been analysed in models with global information and evolution. This study is the first to analyse the leading eight norms with local information and evolution. We find that the leading eight are robust against selfish players within most scenarios and can maintain a high level of cooperation also with local information and evolution. In fact, local evolution sustains cooperation under a wider set of conditions than global evolution, while local reputation does not hinder cooperation compared to global reputation. Four of the leading eight norms that do not reward justified defection offer better chances for cooperation with quick evolution, reputation with noise, larger networks, and when unconditional defectors enter the population.
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41
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Romano A, Saral AS, Wu J. Direct and indirect reciprocity among individuals and groups. Curr Opin Psychol 2021; 43:254-259. [PMID: 34481332 DOI: 10.1016/j.copsyc.2021.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/02/2021] [Accepted: 08/04/2021] [Indexed: 01/10/2023]
Abstract
Direct and indirect reciprocity are two fundamental mechanisms that promote prosocial behavior within groups and across societies. Here, we review recent work that illustrates how a (direct and indirect) reciprocity framework can illuminate our understanding of several factors related to prosocial behavior - namely group membership, gossip, and third-party punishment. We propose that each of these factors can promote prosocial behavior via proximate psychological mechanisms related to direct and indirect reciprocity: reputational concern, expectations, and anticipation of future interaction. Finally, we discuss the implications of adopting such a framework and highlight a number of avenues for future research.
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Affiliation(s)
- Angelo Romano
- Social, Economic and Organizational Psychology, Leiden University, the Netherlands.
| | | | - Junhui Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, China; Department of Psychology, University of Chinese Academy of Sciences, China
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42
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Ma S, Zhang B, Cao S, Liu JS, Wang WX. Limited memory optimizes cooperation in social dilemma experiments. ROYAL SOCIETY OPEN SCIENCE 2021; 8:210653. [PMID: 34457345 PMCID: PMC8385340 DOI: 10.1098/rsos.210653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/29/2021] [Indexed: 06/13/2023]
Abstract
Cooperation is one of the key collective behaviours of human society. Despite discoveries of several social mechanisms underpinning cooperation, relatively little is known about how our neural functions affect cooperative behaviours. Here, we study the effect of a main neural function, working-memory capacity, on cooperation in repeated Prisoner's Dilemma experiments. Our experimental paradigm overcomes the obstacles in measuring and changing subjects' working-memory capacity. We find that the optimal cooperation level occurs when subjects remember two previous rounds of information, and cooperation increases abruptly from no memory capacity to minimal memory capacity. The results can be explained by memory-based conditional cooperation of subjects. We propose evolutionary models based on replicator dynamics and Markov processes, respectively, which are in good agreement with experimental results of different memory capacities. Our experimental findings differ from previous hypotheses and predictions of existent models and theories, and suggest a neural basis and evolutionary roots of cooperation beyond cultural influences.
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Affiliation(s)
- Shuangmei Ma
- School of Systems Science, Beijing Normal University, Beijing 100875, People's Republic of China
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - Boyu Zhang
- Laboratory of Mathematics and Complex Systems, Ministry of Education, School of Mathematical Sciences, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Shinan Cao
- School of Finance, University of International Business and Economics, Beijing 100029, People's Republic of China
| | - Jun S. Liu
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - Wen-Xu Wang
- School of Systems Science, Beijing Normal University, Beijing 100875, People's Republic of China
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, People's Republic of China
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43
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Lee S, Murase Y, Baek SK. Local stability of cooperation in a continuous model of indirect reciprocity. Sci Rep 2021; 11:14225. [PMID: 34244552 PMCID: PMC8270921 DOI: 10.1038/s41598-021-93598-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/28/2021] [Indexed: 02/06/2023] Open
Abstract
Reputation is a powerful mechanism to enforce cooperation among unrelated individuals through indirect reciprocity, but it suffers from disagreement originating from private assessment, noise, and incomplete information. In this work, we investigate stability of cooperation in the donation game by regarding each player's reputation and behaviour as continuous variables. Through perturbative calculation, we derive a condition that a social norm should satisfy to give penalties to its close variants, provided that everyone initially cooperates with a good reputation, and this result is supported by numerical simulation. A crucial factor of the condition is whether a well-reputed player's donation to an ill-reputed co-player is appreciated by other members of the society, and the condition can be reduced to a threshold for the benefit-cost ratio of cooperation which depends on the reputational sensitivity to a donor's behaviour as well as on the behavioural sensitivity to a recipient's reputation. Our continuum formulation suggests how indirect reciprocity can work beyond the dichotomy between good and bad even in the presence of inhomogeneity, noise, and incomplete information.
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Affiliation(s)
- Sanghun Lee
- grid.412576.30000 0001 0719 8994Department of Physics, Pukyong National University, Busan, 48513 Korea
| | - Yohsuke Murase
- grid.474693.bRIKEN Center for Computational Science, Kobe, Hyogo 650-0047 Japan
| | - Seung Ki Baek
- grid.412576.30000 0001 0719 8994Department of Physics, Pukyong National University, Busan, 48513 Korea
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44
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Adherence to public institutions that foster cooperation. Nat Commun 2021; 12:3567. [PMID: 34117236 PMCID: PMC8196024 DOI: 10.1038/s41467-021-23783-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 05/10/2021] [Indexed: 01/30/2023] Open
Abstract
Humans typically consider altruism a moral good and condition their social behavior on the moral reputations of others. Indirect reciprocity explains how social norms and reputations support cooperation: individuals cooperate with others who are considered good. Indirect reciprocity works when an institution monitors and publicly broadcasts moral reputations. Here we develop a theory of adherence to public monitoring in societies where individuals are, at first, independently responsible for evaluating the reputations of their peers. Using a mathematical model, we show that adherence to an institution of moral assessment can evolve and promote cooperation under four different social norms, including norms that previous studies found to perform poorly. We determine how an institution's size and its degree of tolerance towards anti-social behavior affect the rate of cooperation. Public monitoring serves to eliminate disagreements about reputations, which increases cooperation and payoffs, so that adherence evolves by social contagion and remains robust against displacement.
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45
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de Melo CM, Terada K, Santos FC. Emotion expressions shape human social norms and reputations. iScience 2021; 24:102141. [PMID: 33665560 PMCID: PMC7898177 DOI: 10.1016/j.isci.2021.102141] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 01/05/2021] [Accepted: 01/28/2021] [Indexed: 11/19/2022] Open
Abstract
The emergence of pro-social behaviors remains a key open challenge across disciplines. In this context, there is growing evidence that expressing emotions may foster human cooperation. However, it remains unclear how emotions shape individual choices and interact with other cooperation mechanisms. Here, we provide a comprehensive experimental analysis of the interplay of emotion expressions with two important mechanisms: direct and indirect reciprocity. We show that cooperation in an iterated prisoner's dilemma emerges from the combination of the opponent's initial reputation, past behaviors, and emotion expressions. Moreover, all factors influenced the social norm adopted when assessing the action of others - i.e., how their counterparts' reputations are updated - thus, reflecting longer-term consequences. We expose a new class of emotion-based social norms, where emotions are used to forgive those that defect but also punish those that cooperate. These findings emphasize the importance of emotion expressions in fostering, directly and indirectly, cooperation in society.
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Affiliation(s)
| | | | - Francisco C. Santos
- INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, 2744-016 Porto Salvo, Portugal
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Han TA, Pereira LM, Lenaerts T, Santos FC. Mediating artificial intelligence developments through negative and positive incentives. PLoS One 2021; 16:e0244592. [PMID: 33497424 PMCID: PMC7837463 DOI: 10.1371/journal.pone.0244592] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 12/14/2020] [Indexed: 11/18/2022] Open
Abstract
The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, business and also policy. This anxiety is further energised by an AI race narrative that makes people believe they might be missing out. Whether real or not, a belief in this narrative may be detrimental as some stake-holders will feel obliged to cut corners on safety precautions, or ignore societal consequences just to "win". Starting from a baseline model that describes a broad class of technology races where winners draw a significant benefit compared to others (such as AI advances, patent race, pharmaceutical technologies), we investigate here how positive (rewards) and negative (punishments) incentives may beneficially influence the outcomes. We uncover conditions in which punishment is either capable of reducing the development speed of unsafe participants or has the capacity to reduce innovation through over-regulation. Alternatively, we show that, in several scenarios, rewarding those that follow safety measures may increase the development speed while ensuring safe choices. Moreover, in the latter regimes, rewards do not suffer from the issue of over-regulation as is the case for punishment. Overall, our findings provide valuable insights into the nature and kinds of regulatory actions most suitable to improve safety compliance in the contexts of both smooth and sudden technological shifts.
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Affiliation(s)
- The Anh Han
- School of Computing and Digital Technologies, Teesside University, Middlesbrough, United Kingdom
| | - Luís Moniz Pereira
- NOVA Laboratory for Computer Science and Informatics (NOVA LINCS), Universidade Nova de Lisboa, Caparica, Portugal
| | - Tom Lenaerts
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, Brussels, Belgium
- Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Francisco C. Santos
- INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa, Porto, Salvo, Portugal
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Oliveira R, Arriaga P, Santos FP, Mascarenhas S, Paiva A. Towards prosocial design: A scoping review of the use of robots and virtual agents to trigger prosocial behaviour. COMPUTERS IN HUMAN BEHAVIOR 2021. [DOI: 10.1016/j.chb.2020.106547] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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Fernandes PM, Santos FC, Lopes M. Norms for beneficial A.I.: A computational analysis of the societal value alignment problem. AI COMMUN 2020. [DOI: 10.3233/aic-201502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The rise of artificial intelligence (A.I.) based systems is already offering substantial benefits to the society as a whole. However, these systems may also enclose potential conflicts and unintended consequences. Notably, people will tend to adopt an A.I. system if it confers them an advantage, at which point non-adopters might push for a strong regulation if that advantage for adopters is at a cost for them. Here we propose an agent-based game-theoretical model for these conflicts, where agents may decide to resort to A.I. to use and acquire additional information on the payoffs of a stochastic game, striving to bring insights from simulation to what has been, hitherto, a mostly philosophical discussion. We frame our results under the current discussion on ethical A.I. and the conflict between individual and societal gains: the societal value alignment problem. We test the arising equilibria in the adoption of A.I. technology under different norms followed by artificial agents, their ensuing benefits, and the emergent levels of wealth inequality. We show that without any regulation, purely selfish A.I. systems will have the strongest advantage, even when a utilitarian A.I. provides significant benefits for the individual and the society. Nevertheless, we show that it is possible to develop A.I. systems following human conscious policies that, when introduced in society, lead to an equilibrium where the gains for the adopters are not at a cost for non-adopters, thus increasing the overall wealth of the population and lowering inequality. However, as shown, a self-organised adoption of such policies would require external regulation.
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Affiliation(s)
- Pedro M. Fernandes
- INESC-ID and Instituto Superior Técnico, University de Lisboa, Lisbon, Portugal
| | - Francisco C. Santos
- INESC-ID and Instituto Superior Técnico, University de Lisboa, Lisbon, Portugal
| | - Manuel Lopes
- INESC-ID and Instituto Superior Técnico, University de Lisboa, Lisbon, Portugal
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Abstract
Multiplayer games have long been used as testbeds in artificial intelligence research, aptly referred to as the Drosophila of artificial intelligence. Traditionally, researchers have focused on using well-known games to build strong agents. This progress, however, can be better informed by characterizing games and their topological landscape. Tackling this latter question can facilitate understanding of agents and help determine what game an agent should target next as part of its training. Here, we show how network measures applied to response graphs of large-scale games enable the creation of a landscape of games, quantifying relationships between games of varying sizes and characteristics. We illustrate our findings in domains ranging from canonical games to complex empirical games capturing the performance of trained agents pitted against one another. Our results culminate in a demonstration leveraging this information to generate new and interesting games, including mixtures of empirical games synthesized from real world games. Multiplayer games can be used as testbeds for the development of learning algorithms for artificial intelligence. Omidshafiei et al. show how to characterize and compare such games using a graph-based approach, generating new games that could potentially be interesting for training in a curriculum.
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Martinez-Vaquero LA, Santos FC, Trianni V. Signalling boosts the evolution of cooperation in repeated group interactions. J R Soc Interface 2020; 17:20200635. [PMID: 33143593 PMCID: PMC7729056 DOI: 10.1098/rsif.2020.0635] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 10/12/2020] [Indexed: 02/05/2023] Open
Abstract
Many biological and social systems show significant levels of collective action. Several cooperation mechanisms have been proposed, yet they have been mostly studied independently. Among these, direct reciprocity supports cooperation on the basis of repeated interactions among individuals. Signals and quorum dynamics may also drive cooperation. Here, we resort to an evolutionary game-theoretical model to jointly analyse these two mechanisms and study the conditions in which evolution selects for direct reciprocity, signalling, or their combination. We show that signalling alone leads to higher levels of cooperation than when combined with reciprocity, while offering additional robustness against errors. Specifically, successful strategies in the realm of direct reciprocity are often not selected in the presence of signalling, and memory of past interactions is only exploited opportunistically in the case of earlier coordination failure. Differently, signalling always evolves, even when costly. In the light of these results, it may be easier to understand why direct reciprocity has been observed only in a limited number of cases among non-humans, whereas signalling is widespread at all levels of complexity.
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Affiliation(s)
- Luis A. Martinez-Vaquero
- Institute of Cognitive Sciences and Technologies National Research Council of Italy, via San Martino della Battaglia 44, 00185 Rome, Italy
| | - Francisco C. Santos
- INESC-ID Lisboa and Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
| | - Vito Trianni
- Institute of Cognitive Sciences and Technologies National Research Council of Italy, via San Martino della Battaglia 44, 00185 Rome, Italy
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