1
|
Fiedler S, Habibnia H, Fahrenwaldt A, Rahal RM. Motivated Cognition in Cooperation. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2024; 19:385-403. [PMID: 37883800 PMCID: PMC10913374 DOI: 10.1177/17456916231193990] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Successful cooperation is tightly linked to individuals' beliefs about their interaction partners, the decision setting, and existing norms, perceptions, and values. This article reviews and integrates findings from judgment and decision-making, social and cognitive psychology, political science, and economics, developing a systematic overview of the mechanisms underlying motivated cognition in cooperation. We elaborate on how theories and concepts related to motivated cognition developed in various disciplines define the concept and describe its functionality. We explain why beliefs play such an essential role in cooperation, how they can be distorted, and how this fosters or harms cooperation. We also highlight how individual differences and situational factors change the propensity to engage in motivated cognition. In the form of a construct map, we provide a visualization of the theoretical and empirical knowledge structure regarding the role of motivated cognition, including its many interdependencies, feedback loops, and moderating influences. We conclude with a brief suggestion for a future research agenda based on this compiled evidence.
Collapse
Affiliation(s)
- Susann Fiedler
- Vienna University of Economics and Business, Austria
- Max Planck Institute for Research on Collective Goods, Bonn, Germany
| | | | - Alina Fahrenwaldt
- Max Planck Institute for Research on Collective Goods, Bonn, Germany
- Faculty of Human Sciences, University of Cologne, Germany
| | - Rima-Maria Rahal
- Max Planck Institute for Research on Collective Goods, Bonn, Germany
| |
Collapse
|
2
|
Hua S, Hui Z, Liu L. Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions. Proc Biol Sci 2023; 290:20230949. [PMID: 37670581 PMCID: PMC10510442 DOI: 10.1098/rspb.2023.0949] [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: 04/25/2023] [Accepted: 08/14/2023] [Indexed: 09/07/2023] Open
Abstract
The evolution and long-term sustenance of cooperation has consistently piqued scholarly interest across the disciplines of evolutionary biology and social sciences. Previous theoretical and experimental studies on collective risk social dilemma games have revealed that the risk of collective failure will affect the evolution of cooperation. In the real world, individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level. However, it is still not well understood how such conditional behaviours affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes, with a high risk promoting the emergence of cooperation. Importantly, when the risk of failure to reach collective goals exceeds a certain threshold, the timely transition from a defective strategy to a cooperative strategy by conditional cooperators is beneficial for maintaining high-level cooperation.
Collapse
Affiliation(s)
- Shijia Hua
- College of Science, Northwest A & F University, Yangling 712100, People’s Republic of China
| | - Zitong Hui
- College of Science, Northwest A & F University, Yangling 712100, People’s Republic of China
| | - Linjie Liu
- College of Science, Northwest A & F University, Yangling 712100, People’s Republic of China
| |
Collapse
|
3
|
Meng Y, Broom M, Li A. Impact of misinformation in the evolution of collective cooperation on networks. J R Soc Interface 2023; 20:20230295. [PMID: 37751874 PMCID: PMC10522409 DOI: 10.1098/rsif.2023.0295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 09/04/2023] [Indexed: 09/28/2023] Open
Abstract
Human societies are organized and developed through collective cooperative behaviours. Based on the information in their environment, individuals can form collective cooperation by strategically changing unfavourable surroundings and imitating superior behaviours. However, facing the rampant proliferation and spreading of misinformation, we still lack systematic investigations into the impact of misinformation on the evolution of collective cooperation. Here, we study this problem by classical evolutionary game theory. We find that the existence of misinformation generally impedes the emergence of collective cooperation on networks, although the level of cooperation is slightly higher for weak social cooperative dilemma below a proven threshold. We further show that this possible advantage diminishes as social connections become denser, suggesting that the detrimental effect of misinformation further increases when 'social viscosity' is low. Our results uncover the quantitative effect of misinformation on suppressing collective cooperation, and pave the way for designing possible mechanisms to improve collective cooperation.
Collapse
Affiliation(s)
- Yao Meng
- Center for Systems and Control, College of Engineering, Peking University, Beijing 100871, People’s Republic of China
| | - Mark Broom
- Department of Mathematics, City, University of London, Northampton Square, London EC1V 0HB, UK
| | - Aming Li
- 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
| |
Collapse
|
4
|
Barfuss W, Meylahn JM. Intrinsic fluctuations of reinforcement learning promote cooperation. Sci Rep 2023; 13:1309. [PMID: 36693872 PMCID: PMC9873645 DOI: 10.1038/s41598-023-27672-7] [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: 10/26/2022] [Accepted: 01/05/2023] [Indexed: 01/26/2023] Open
Abstract
In this work, we ask for and answer what makes classical temporal-difference reinforcement learning with [Formula: see text]-greedy strategies cooperative. Cooperating in social dilemma situations is vital for animals, humans, and machines. While evolutionary theory revealed a range of mechanisms promoting cooperation, the conditions under which agents learn to cooperate are contested. Here, we demonstrate which and how individual elements of the multi-agent learning setting lead to cooperation. We use the iterated Prisoner's dilemma with one-period memory as a testbed. Each of the two learning agents learns a strategy that conditions the following action choices on both agents' action choices of the last round. We find that next to a high caring for future rewards, a low exploration rate, and a small learning rate, it is primarily intrinsic stochastic fluctuations of the reinforcement learning process which double the final rate of cooperation to up to 80%. Thus, inherent noise is not a necessary evil of the iterative learning process. It is a critical asset for the learning of cooperation. However, we also point out the trade-off between a high likelihood of cooperative behavior and achieving this in a reasonable amount of time. Our findings are relevant for purposefully designing cooperative algorithms and regulating undesired collusive effects.
Collapse
Affiliation(s)
- Wolfram Barfuss
- Tübingen AI Center, University of Tübingen, Tübingen, Germany
| | - Janusz M Meylahn
- Department of Applied Mathematics, University of Twente, Enschede, The Netherlands. .,Dutch Institute of Emergent Phenomena, University of Amsterdam, Amsterdam, The Netherlands.
| |
Collapse
|
5
|
Ecker U, Sanderson JA, McIlhiney P, Rowsell JJ, Quekett HL, Brown G, Lewandowsky S. EXPRESS: Combining Refutations and Social Norms Increases Belief Change. Q J Exp Psychol (Hove) 2022; 76:1275-1297. [PMID: 35748514 DOI: 10.1177/17470218221111750] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Misinformed beliefs are difficult to change. Refutations that target false claims typically reduce false beliefs, but tend to be only partially effective. In this study, a social norming approach was explored to test whether provision of peer norms could provide an alternative or complementary approach to refutation. Three experiments investigated whether a descriptive norm-by itself or in combination with a refutation-could reduce the endorsement of worldview-congruent claims. Experiment 1 found that using a single point estimate to communicate a norm affected belief but had less impact than a refutation. Experiment 2 used a verbally-presented distribution of four values to communicate a norm, which was largely ineffective. Experiment 3 used a graphically-presented social norm with 25 values, which was found to be as effective at reducing claim belief as a refutation, with the combination of both interventions being most impactful. These results provide a proof of concept that normative information can aid in the debunking of false or equivocal claims, and suggests that theories of misinformation processing should take social factors into account.
Collapse
Affiliation(s)
- Ullrich Ecker
- School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia 2720
| | - Jasmyne A Sanderson
- School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia 2720
| | - Paul McIlhiney
- School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia 2720
| | - Jessica J Rowsell
- School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia 2720
| | - Hayley L Quekett
- School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia 2720
| | - Gordon Brown
- Department of Psychology, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, United Kingdom 2707
| | - Stephan Lewandowsky
- School of Psychological Science, University of Bristol, 12a Priory Road, Bristol BS8 1TU, United Kingdom 1980.,School of Psychological Science, University of Western Australia, 35 Stirling Hwy, Perth 6009, Australia
| |
Collapse
|
6
|
Sun W, Liu L, Chen X, Szolnoki A, Vasconcelos VV. Combination of institutional incentives for cooperative governance of risky commons. iScience 2021; 24:102844. [PMID: 34381969 PMCID: PMC8334382 DOI: 10.1016/j.isci.2021.102844] [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] [Received: 05/10/2021] [Revised: 06/23/2021] [Accepted: 07/08/2021] [Indexed: 11/03/2022] Open
Abstract
Finding appropriate incentives to enforce collaborative efforts for governing the commons in risky situations is a long-lasting challenge. Previous works have demonstrated that both punishing free-riders and rewarding cooperators could be potential tools to reach this goal. Despite weak theoretical foundations, policy makers frequently impose a punishment-reward combination. Here, we consider the emergence of positive and negative incentives and analyze their simultaneous impact on sustaining risky commons. Importantly, we consider institutions with fixed and flexible incentives. We find that a local sanctioning scheme with pure reward is the optimal incentive strategy. It can drive the entire population toward a highly cooperative state in a broad range of parameters, independently of the type of institutions. We show that our finding is also valid for flexible incentives in the global sanctioning scheme, although the local arrangement works more effectively. Pure reward in a local scheme is more effective both for fixed and flexible incentives It can drive the entire population toward a highly cooperative state Increasing the efficiency of the institution can induce the success of pure reward A local scheme promotes group success more effectively than a global scheme
Collapse
Affiliation(s)
- Weiwei Sun
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Linjie Liu
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xiaojie Chen
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Attila Szolnoki
- Institute of Technical Physics and Materials Science, Centre for Energy Research, P.O. Box 49, Budapest 1525, Hungary
| | - Vítor V Vasconcelos
- Informatics Institute, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands.,Institute for Advanced Study, University of Amsterdam, 1012 GC Amsterdam, The Netherlands
| |
Collapse
|