Swarm intelligence in animal groups: when can a collective out-perform an expert?

How Approaches to Animal Swarm Intelligence Can Improve the Study of Collective Intelligence in Human Teams

Researchers of team behavior have long been interested in the essential components of effective teamwork. Much existing research focuses on examining correlations between team member traits, team processes, and team outcomes, such as collective intelligence or team performance. However, these approaches are insufficient for providing insight into the dynamic, causal mechanisms through which the components of teamwork interact with one another and impact the emergence of team outcomes. Advances in the field of animal behavior have enabled a precise understanding of the behavioral mechanisms that enable groups to perform feats that surpass the capabilities of the individuals that comprise them. In this manuscript, we highlight how studies of animal swarm intelligence can inform research on collective intelligence in human teams. By improving the ability to obtain precise, time-varying measurements of team behaviors and outcomes and building upon approaches used in studies of swarm intelligence to analyze and model individual and group-level behaviors, researchers can gain insight into the mechanisms underlying the emergence of collective intelligence. Such understanding could inspire targeted interventions to improve team effectiveness and support the development of a comparative framework of group-level intelligence in animal and human groups.

Decision-Making Processes Underlying Pedestrian Behaviors at Signalized Crossings: Part 2. Do Pedestrians Show Cultural Herding Behavior?

Followership is generally defined as a strategy that evolved to solve social coordination problems, and particularly those involved in group movement. Followership behavior is particularly interesting in the context of road-crossing behavior because it involves other principles such as risk-taking and evaluating the value of social information. This study sought to identify the cognitive mechanisms underlying decision-making by pedestrians who follow another person across the road at the green or at the red light in two different countries (France and Japan). We used agent-based modelling to simulate the road-crossing behaviors of pedestrians. This study showed that modelling is a reliable means to test different hypotheses and find the processes underlying decision-making when crossing the road. We found that two processes suffice to simulate pedestrian behaviors: personal motivation and imitation. Importantly, the study revealed differences between the two nationalities and between sexes in the decision to follow and cross at the green and at the red light. Japanese pedestrians showed a greater mimetic behavior at the red light but the process takes into account both the number of crossing and waiting pedestrians, contrary to French citizens. Finally, the simulations are revealed to be similar to observations, not only for the departure latencies but also for the number of crossing pedestrians and the rates of illegal crossings. The conclusion suggests new solutions for safety in transportation research.

Quorums enable optimal pooling of independent judgements in biological systems

Collective decision-making is ubiquitous, and majority-voting and the Condorcet Jury Theorem pervade thinking about collective decision-making. Thus, it is typically assumed that majority-voting is the best possible decision mechanism, and that scenarios exist where individually-weak decision-makers should not pool information. Condorcet and its applications implicitly assume that only one kind of error can be made, yet signal detection theory shows two kinds of errors exist, 'false positives' and 'false negatives'. We apply signal detection theory to collective decision-making to show that majority voting is frequently sub-optimal, and can be optimally replaced by quorum decision-making. While quorums have been proposed to resolve within-group conflicts, or manage speed-accuracy trade-offs, our analysis applies to groups with aligned interests undertaking single-shot decisions. Our results help explain the ubiquity of quorum decision-making in nature, relate the use of sub- and super-majority quorums to decision ecology, and may inform the design of artificial decision-making systems.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Individual Confidence-Weighting and Group Decision-Making

Group-living species frequently pool individual information so as to reach consensus decisions such as when and where to move, or whether a predator is present. Such opinion-pooling has been demonstrated empirically, and theoretical models have been proposed to explain why group decisions are more reliable than individual decisions. Behavioural ecology theory frequently assumes that all individuals have equal decision-making abilities, but decision theory relaxes this assumption and has been tested in human groups. We summarise relevant theory and argue for its applicability to collective animal decisions. We consider selective pressure on confidence-weighting in groups of related and unrelated individuals. We also consider which species and behaviours may provide evidence of confidence-weighting, paying particular attention to the sophisticated vocal communication of cooperative breeders.

Social density processes regulate the functioning and performance of foraging human teams

Social density processes impact the activity and order of collective behaviours in a variety of biological systems. Much effort has been devoted to understanding how density of people affects collective human motion in the context of pedestrian flows. However, there is a distinct lack of empirical data investigating the effects of social density on human behaviour in cooperative contexts. Here, we examine the functioning and performance of human teams in a central-place foraging arena using high-resolution GPS data. We show that team functioning (level of coordination) is greatest at intermediate social densities, but contrary to our expectations, increased coordination at intermediate densities did not translate into improved collective foraging performance, and foraging accuracy was equivalent across our density treatments. We suggest that this is likely a consequence of foragers relying upon visual channels (local information) to achieve coordination but relying upon auditory channels (global information) to maximise foraging returns. These findings provide new insights for the development of more sophisticated models of human collective behaviour that consider different networks for communication (e.g. visual and vocal) that have the potential to operate simultaneously in cooperative contexts.

Ants work harder during consensus decision-making in small groups

Individuals derive many benefits from being social, one of which is improved accuracy of decision-making, the so-called 'wisdom of the crowds' effect. This advantage arises because larger groups can pool information from more individuals. At present, limited empirical data indicate that larger groups outperform smaller ones during consensus decision-making in human and non-human animals. Inaccurate decisions can lead to significant costs, and we might therefore expect individuals in small groups to employ mechanisms to compensate for the lack of numbers. Small groups may be able to maintain decision accuracy if individuals are better informed than those in larger groups and/or by increasing the proportion of the group involved in collective decision-making relative to larger groups. In this study, we use interactive computer vision software to investigate individual contributions to consensus decision-making during house-hunting in different sized groups of the ant Myrmecina nipponica. We show that individuals in small colonies invest greater effort in the consensus decision process than those in large colonies and should be better informed as a result. This may act to ameliorate the limitations of group size, but could leave smaller groups more susceptible to additional stresses.

Social cognition in fishes

Brain evolution has often been correlated with the cognitive demands of social life. Further progress depends on our ability to link cognitive processes to corresponding brain part sizes and structures, and, ultimately, to demonstrate causality. Recent research suggests that fishes are suitable to test general hypotheses about vertebrate social cognition and its evolution: brain structure and physiology are rather conserved among vertebrates, and fish are able to perform complex decisions in social context. Here, we outline the opportunities for experimentation and comparative studies using fish as model systems, as well as some current shortcomings in fish social cognition research.

Collective decision-making in microbes

Microbes are intensely social organisms that routinely cooperate and coordinate their activities to express elaborate population level phenotypes. Such coordination requires a process of collective decision-making, in which individuals detect and collate information not only from their physical environment, but also from their social environment, in order to arrive at an appropriately calibrated response. Here, we present a conceptual overview of collective decision-making as it applies to all group-living organisms; we introduce key concepts and principles developed in the context of animal and human group decisions; and we discuss, with appropriate examples, the applicability of each of these concepts in microbial contexts. In particular, we discuss the roles of information pooling, control skew, speed vs. accuracy trade-offs, local feedbacks, quorum thresholds, conflicts of interest, and the reliability of social information. We conclude that collective decision-making in microbes shares many features with collective decision-making in higher taxa, and we call for greater integration between this fledgling field and other allied areas of research, including in the humanities and the physical sciences.

Pathogen intelligence

Different species inhabit different sensory worlds and thus have evolved diverse means of processing information, learning and memory. In the escalated arms race with host defense, each pathogenic bacterium not only has evolved its individual cellular sensing and behavior, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behavior, and the phenotypic and genotypic heterogeneity necessary for epidemiologic success. Moreover, pathogenic populations take advantage of dormancy strategies and rapid evolutionary speed, which allow them to save co-generated intelligent traits in a collective genomic memory. This review discusses how these mechanisms add further levels of complexity to bacterial pathogenicity and transmission, and how mining for these mechanisms could help to develop new anti-infective strategies.

When none of us perform better than all of us together: the role of analogical decision rules in groups

During social interactions, groups develop collective competencies that (ideally) should assist groups to outperform average standalone individual members (weak cognitive synergy) or the best performing member in the group (strong cognitive synergy). In two experimental studies we manipulate the type of decision rule used in group decision-making (identify the best vs. collaborative), and the way in which the decision rules are induced (direct vs. analogical) and we test the effect of these two manipulations on the emergence of strong and weak cognitive synergy. Our most important results indicate that an analogically induced decision rule (imitate-the-successful heuristic) in which groups have to identify the best member and build on his/her performance (take-the-best heuristic) is the most conducive for strong cognitive synergy. Our studies bring evidence for the role of analogy-making in groups as well as the role of fast-and-frugal heuristics for group decision-making.

Collective animal decisions: preference conflict and decision accuracy

Social animals frequently share decisions that involve uncertainty and conflict. It has been suggested that conflict can enhance decision accuracy. In order to judge the practical relevance of such a suggestion, it is necessary to explore how general such findings are. Using a model, I examine whether conflicts between animals in a group with respect to preferences for avoiding false positives versus avoiding false negatives could, in principle, enhance the accuracy of collective decisions. I found that decision accuracy nearly always peaked when there was maximum conflict in groups in which individuals had different preferences. However, groups with no preferences were usually even more accurate. Furthermore, a relatively slight skew towards more animals with a preference for avoiding false negatives decreased the rate of expected false negatives versus false positives considerably (and vice versa), while resulting in only a small loss of decision accuracy. I conclude that in ecological situations in which decision accuracy is crucial for fitness and survival, animals cannot 'afford' preferences with respect to avoiding false positives versus false negatives. When decision accuracy is less crucial, animals might have such preferences. A slight skew in the number of animals with different preferences will result in the group avoiding that type of error more that the majority of group members prefers to avoid. The model also indicated that knowing the average success rate ('base rate') of a decision option can be very misleading, and that animals should ignore such base rates unless further information is available.

Collective cognition in humans: groups outperform their best members in a sentence reconstruction task

Group-living is widespread among animals and one of the major advantages of group-living is the ability of groups to solve cognitive problems that exceed individual ability. Humans also make use of collective cognition and have simultaneously developed a highly complex language to exchange information. Here we investigated collective cognition of human groups regarding language use in a realistic situation. Individuals listened to a public announcement and had to reconstruct the sentence alone or in groups. This situation is often encountered by humans, for instance at train stations or airports. Using recent developments in machine speech recognition, we analysed how well individuals and groups reconstructed the sentences from a syntactic (i.e., the number of errors) and semantic (i.e., the quality of the retrieved information) perspective. We show that groups perform better both on a syntactic and semantic level than even their best members. Groups made fewer errors and were able to retrieve more information when reconstructing the sentences, outcompeting even their best group members. Our study takes collective cognition studies to the more complex level of language use in humans.

Swarm intelligence: when uncertainty meets conflict

Good decision making is important for the survival and fitness of stakeholders, but decisions usually involve uncertainty and conflict. We know surprisingly little about profitable decision-making strategies in conflict situations. On the one hand, sharing decisions with others can pool information and decrease uncertainty (swarm intelligence). On the other hand, sharing decisions can hand influence to individuals whose goals conflict. Thus, when should an animal share decisions with others? Using a theoretical model, we show that, contrary to intuition, decision sharing by animals with conflicting goals often increases individual gains as well as decision accuracy. Thus, conflict-far from hampering effective decision making-can improve decision outcomes for all stakeholders, as long as they share large-scale goals. In contrast, decisions shared by animals without conflict were often surprisingly poor. The underlying mechanism is that animals with conflicting goals are less correlated in individual choice errors. These results provide a strong argument in the interest of all stakeholders for not excluding other (e.g., minority) factions from collective decisions. The observed benefits of including diverse factions among the decision makers could also be relevant to human collective decision making.

Decision rules and group rationality: cognitive gain or standstill?

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.

When does diversity trump ability (and vice versa) in group decision making? A simulation study

It is often unclear which factor plays a more critical role in determining a group's performance: the diversity among members of the group or their individual abilities. In this study, we addressed this "diversity vs. ability" issue in a decision-making task. We conducted three simulation studies in which we manipulated agents' individual ability (or accuracy, in the context of our investigation) and group diversity by varying (1) the heuristics agents used to search task-relevant information (i.e., cues); (2) the size of their groups; (3) how much they had learned about a good cue search order; and (4) the magnitude of errors in the information they searched. In each study, we found that a manipulation reducing agents' individual accuracy simultaneously increased their group's diversity, leading to a conflict between the two. These conflicts enabled us to identify certain conditions under which diversity trumps individual accuracy, and vice versa. Specifically, we found that individual accuracy is more important in task environments in which cues differ greatly in the quality of their information, and diversity matters more when such differences are relatively small. Changing the size of a group and the amount of learning by an agent had a limited impact on this general effect of task environment. Furthermore, we found that a group achieves its highest accuracy when there is an intermediate amount of errors in the cue information, regardless of the environment and the heuristic used, an effect that we believe has not been previously reported and warrants further investigation.

Models in animal collective decision-making: information uncertainty and conflicting preferences

Collective decision-making plays a central part in the lives of many social animals. Two important factors that influence collective decision-making are information uncertainty and conflicting preferences. Here, I bring together, and briefly review, basic models relating to animal collective decision-making in situations with information uncertainty and in situations with conflicting preferences between group members. The intention is to give an overview about the different types of modelling approaches that have been employed and the questions that they address and raise. Despite the use of a wide range of different modelling techniques, results show a coherent picture, as follows. Relatively simple cognitive mechanisms can lead to effective information pooling. Groups often face a trade-off between decision accuracy and speed, but appropriate fine-tuning of behavioural parameters could achieve high accuracy while maintaining reasonable speed. The right balance of interdependence and independence between animals is crucial for maintaining group cohesion and achieving high decision accuracy. In conflict situations, a high degree of decision-sharing between individuals is predicted, as well as transient leadership and leadership according to needs and physiological status. Animals often face crucial trade-offs between maintaining group cohesion and influencing the decision outcome in their own favour. Despite the great progress that has been made, there remains one big gap in our knowledge: how do animals make collective decisions in situations when information uncertainty and conflict of interest operate simultaneously?

Collective irrationality and positive feedback

Recent experiments on ants and slime moulds have assessed the degree to which they make rational decisions when presented with a number of alternative food sources or shelter. Ants and slime moulds are just two examples of a wide range of species and biological processes that use positive feedback mechanisms to reach decisions. Here we use a generic, experimentally validated model of positive feedback between group members to show that the probability of taking the best of options depends crucially on the strength of feedback. We show how the probability of choosing the best option can be maximized by applying an optimal feedback strength. Importantly, this optimal value depends on the number of options, so that when we change the number of options the preference of the group changes, producing apparent “irrationalities”. We thus reinterpret the idea that collectives show "rational" or "irrational" preferences as being a necessary consequence of the use of positive feedback. We argue that positive feedback is a heuristic which often produces fast and accurate group decision-making, but is always susceptible to apparent irrationality when studied under particular experimental conditions.