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.

The ecology of competition: A theory of risk-reward environments in adaptive decision making.

In many choice environments, risks and rewards-or probabilities and payoffs-seem tightly coupled such that high payoffs only occur with low probabilities. An adaptive mind can exploit this association by, for instance, using a potential reward's size to infer the probability of obtaining it. However, a mind can only adapt to and exploit an environmental structure if it is ecologically reliable, that is if it is frequent and recurrent. We develop the competitive risk-reward ecology theory (CET) that establishes how the ecology of competition can make the association of high rewards with low probabilities ubiquitous. This association occurs because of what is known as the ideal free distribution (IFD) principle. The IFD states that competitors in a landscape of resource patches distribute themselves proportionally to the gross total amount of resources in the patches. CET shows how this principle implies a risk-reward structure: an inverse relationship between probabilities and payoffs. It also identifies boundary conditions for the risk-reward structure, including heterogeneity of resources, computational limits of competitors, and scarcity of resources. Finally, a set of empirical studies (N = 1,255) demonstrate that people's beliefs map onto properties predicted by CET and change as a function of the environment. In sum, grounding people's inferences in CET demonstrates how the behaviors of a boundedly rational mind can be better predicted once accounts of the mind and the environment are fused. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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.

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?

Uninformed individuals promote democratic consensus in animal groups.

Conflicting interests among group members are common when making collective decisions, yet failure to achieve consensus can be costly. Under these circumstances individuals may be susceptible to manipulation by a strongly opinionated, or extremist, minority. It has previously been argued, for humans and animals, that social groups containing individuals who are uninformed, or exhibit weak preferences, are particularly vulnerable to such manipulative agents. Here, we use theory and experiment to demonstrate that, for a wide range of conditions, a strongly opinionated minority can dictate group choice, but the presence of uninformed individuals spontaneously inhibits this process, returning control to the numerical majority. Our results emphasize the role of uninformed individuals in achieving democratic consensus amid internal group conflict and informational constraints.

Deciding group movements: where and when to go.

A group of animals can only move cohesively, if group members "somehow" reach a consensus about the timing (e.g., start) and the spatial direction/destination of the collective movement. Timing and spatial decisions usually differ with respect to the continuity of their cost/benefit distribution in such a way that, in principle, compromises are much more feasible in timing decision (e.g., median preferred time) than they are in spatial decisions. The consequence is that consensus costs connected to collective timing decisions are usually less skewed amongst group members than are consensus costs connected to spatial decisions. This, in turn, influences the evolution of decision sharing: sharing in timing decisions is most likely to evolve when conflicts are high relative to group cohesion benefits, while sharing in spatial decisions is most likely to evolve in the opposite situation. We discuss the implications of these differences for the study of collective movement decisions.

Group decisions in humans and animals: a survey.

Humans routinely make many decisions collectively, whether they choose a restaurant with friends, elect political leaders or decide actions to tackle international problems, such as climate change, that affect the future of the whole planet. We might be less aware of it, but group decisions are just as important to social animals as they are for us. Animal groups have to collectively decide about communal movements, activities, nesting sites and enterprises, such as cooperative breeding or hunting, that crucially affect their survival and reproduction. While human group decisions have been studied for millennia, the study of animal group decisions is relatively young, but is now expanding rapidly. It emerges that group decisions in animals pose many similar questions to those in humans. The purpose of the present issue is to integrate and combine approaches in the social and natural sciences in an area in which theoretical challenges and research questions are often similar, and to introduce each discipline to the other's key ideas, findings and successful methods. In order to make such an introduction as effective as possible, here, we briefly review conceptual similarities and differences between the sciences, and provide a guide to the present issue.

Conflicts of interest and the evolution of decision sharing.

Social animals regularly face consensus decisions whereby they choose, collectively, between mutually exclusive actions. Such decisions often involve conflicts of interest between group members with respect to preferred action. Conflicts could, in principle, be resolved, either by sharing decisions between members ('shared decisions') or by one 'dominant' member making decisions on behalf of the whole group ('unshared decisions'). Both, shared and unshared decisions, have been observed. However, it is unclear as to what favours the evolution of either decision type. Here, after a brief literature review, we present a novel method, involving a combination of self-organizing system and game theory modelling, of investigating the evolution of shared and unshared decisions. We apply the method to decisions on movement direction. We find that both, shared and unshared, decisions can evolve without individuals having a global overview of the group's behaviour or any knowledge about other members' preferences or intentions. Selection favours unshared over shared decisions when conflicts are high relative to grouping benefits, and vice versa. These results differ from those of group decision models relating to activity timings. We attribute this to fundamental differences between collective decisions about modalities that are disjunct (here, space) or continuous (here, time) with respect to costs/benefits.

Group decisions: how (not) to choose a restaurant with friends.

Subordinate baboons voluntarily follow the dominant group member to foraging patches where they themselves starve. One-sided preservation of social ties seems to prevail over fair decision sharing, contradicting recent theory.

Integrating individual movement behaviour into dispersal functions.

Dispersal functions are an important tool for integrating dispersal into complex models of population and metapopulation dynamics. Most approaches in the literature are very simple, with the dispersal functions containing only one or two parameters which summarise all the effects of movement behaviour as for example different movement patterns or different perceptual abilities. The summarising nature of these parameters makes assessing the effect of one particular behavioural aspect difficult. We present a way of integrating movement behavioural parameters into a particular dispersal function in a simple way. Using a spatial individual-based simulation model for simulating different movement behaviours, we derive fitting functions for the functional relationship between the parameters of the dispersal function and several details of movement behaviour. This is done for three different movement patterns (loops, Archimedean spirals, random walk). Additionally, we provide measures which characterise the shape of the dispersal function and are interpretable in terms of landscape connectivity. This allows an ecological interpretation of the relationships found.

Consensus decision making in animals.

Individual animals routinely face decisions that are crucial to their fitness. In social species, however, many of these decisions need to be made jointly with other group members because the group will split apart unless a consensus is reached. Here, we review empirical and theoretical studies of consensus decision making, and place them in a coherent framework. In particular, we classify consensus decisions according to the degree to which they involve conflict of interest between group members, and whether they involve either local or global communication; we ask, for different categories of consensus decision, who makes the decision, what are the underlying mechanisms, and what are the functional consequences. We conclude that consensus decision making is common in non-human animals, and that cooperation between group members in the decision-making process is likely to be the norm, even when the decision involves significant conflict of interest.