Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

Condorcet''s jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees'' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees.     

Leadership,consensus decision making and collective behaviour in humans

This paper reviews the literature on leadership in vertebrate groups, including recent work on human groups, before presenting the results of three new experiments looking at leadership and decision making in small and large human groups. In experiment 1, we find that both group size and the presence of uninformed individuals can affect the speed with which small human groups (eight people) decide between two opposing directional preferences and the likelihood of the group splitting. In experiment 2, we show that the spatial positioning of informed individuals within small human groups (10 people) can affect the speed and accuracy of group motion. We find that having a mixture of leaders positioned in the centre and on the edge of a group increases the speed and accuracy with which the group reaches their target. In experiment 3, we use large human crowds (100 and 200 people) to demonstrate that the trends observed from earlier work using small human groups can be applied to larger crowds. We find that only a small minority of informed individuals is needed to guide a large uninformed group. These studies build upon important theoretical and empirical work on leadership and decision making in animal groups.     

Quorum sensing by encounter rates in the ant Temnothorax albipennis

Emigrating colonies of the ant Temnothorax (formerly Leptothorax)albipennis can choose the best of several nest sites, even whenthe active ants organizing the move do not compare sites. Thiscollective ability depends on a quorum rule used by ants assessinga candidate site. Only when the site's population has surpasseda threshold do they switch from slow recruitment of fellow activeants by tandem runs to rapid transport of the majority of thecolony. Here, I show that ants perceive the achievement of aquorum through their rate of direct encounters with nest matesat the site. When ants in a crowded site were prevented fromtactile contact with nest mates, they recruited by tandem runs,as though to an empty nest. Furthermore, when the encounterrate was raised independent of population, by reducing the sizeof the candidate nest, ants started to transport at a significantlylower population. The switch occurred at the same encounterrate regardless of nest size, whether the rate was measuredas the mean over the entire visit or as the inverse of the latencyuntil the first encounter. Because encounter rate reflects thedensity of nest mates and thus varies with nest size as wellas population, the ants' collective decision-making algorithmmay be robust to the exact population at which the switch totransport occurs. Ants cease monitoring quorum presence afterswitching to transport, coincident with an abrupt shorteningof visit duration by approximately 2 min, which may be interpretedas the time required for quorum detection.     

The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy

Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions (an effect we call stalemate filtering). In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemate filtering for improving the decision-making abilities of group-living animals.     

Implementing shared decision making in routine mental health care

Shared decision making (SDM) in mental health care involves clinicians and patients working together to make decisions. The key elements of SDM have been identified, decision support tools have been developed, and SDM has been recommended in mental health at policy level. Yet implementation remains limited. Two justifications are typically advanced in support of SDM. The clinical justification is that SDM leads to improved outcome, yet the available empirical evidence base is inconclusive. The ethical justification is that SDM is a right, but clinicians need to balance the biomedical ethical principles of autonomy and justice with beneficence and non‐maleficence. It is argued that SDM is “polyvalent”, a sociological concept which describes an idea commanding superficial but not deep agreement between disparate stakeholders. Implementing SDM in routine mental health services is as much a cultural as a technical problem. Three challenges are identified: creating widespread access to high‐quality decision support tools; integrating SDM with other recovery‐supporting interventions; and responding to cultural changes as patients develop the normal expectations of citizenship. Two approaches which may inform responses in the mental health system to these cultural changes – social marketing and the hospitality industry – are identified.     

Multimodal signals enhance decision making in foraging bumble-bees

Multimodal signals are common in nature and have recently attracted considerable attention. Despite this interest, their function is not well understood. We test the hypothesis that multimodal signals improve decision making in receivers by influencing the speed and the accuracy of their decisions. We trained bumble-bees (Bombus impatiens) to discriminate between artificial flowers that differed either in one modality, visual (specifically, shape) or olfactory, or in two modalities, visual plus olfactory. Bees trained on multimodal flowers learned the rewarding flowers faster than those trained on flowers that differed only in the visual modality and, in extinction trials, visited the previously rewarded flowers at a higher rate than bees trained on unimodal flowers. Overall, bees showed a speed-accuracy trade-off; bees that made slower decisions achieved higher accuracy levels. Foraging on multimodal flowers did not affect the slope of the speed-accuracy relationship, but resulted in a higher intercept, indicating that multimodal signals were associated with consistently higher accuracy across range of decision speeds. Our results suggest that bees make more effective decisions when flowers signal in more than one modality, and confirm the importance of studying signal components together rather than separately.     

Short term response is predictive of long term response to acetylcholinesterase inhibitors in Alzheimer’s disease: A starting point to explore Bayesian approximation in clinical practice

This study was aimed at identifying, in 203 patients with Alzheimer''s disease followed during long-term treatment with Acetylcholinesterase inhibitors (ChEIs), the predictive factors of the clinical response among cognition (MMSE), functioning (BADL and IADL) measures and age and gender at the baseline (T0). The ANCOVA test showed a significant association between MMSE scores at time T0 and T3, and the variation T9 to T0, T15 to T0 and T21 to T0 of the MMSE scores, using also gender, age and drug as covariates. The significance was higher for the patients affected by mild dementia. Regarding functional activities, a significant relationship was detected, by the ANCOVA test, only between the scores at T3 and the variation T15 to T0 for BADL, and the variation T9 to T0, T15 to T0 for IADL, respectively. Our results confirm, in a real world setting, that ChEIs provide long-term cognitive benefit, which is correlated to, and predictable by, the short-term response (within the third month) as well as the cognitive status (evaluated by means of the MMSE) at the beginning of the treatment. These factors should be the basis of any cost/effectiveness algorithm in health economic decision models.     

The importance of mechanisms for the evolution of cooperation

Studies aimed at explaining the evolution of phenotypic traits have often solely focused on fitness considerations, ignoring underlying mechanisms. In recent years, there has been an increasing call for integrating mechanistic perspectives in evolutionary considerations, but it is not clear whether and how mechanisms affect the course and outcome of evolution. To study this, we compare four mechanistic implementations of two well-studied models for the evolution of cooperation, the Iterated Prisoner''s Dilemma (IPD) game and the Iterated Snowdrift (ISD) game. Behavioural strategies are either implemented by a 1 : 1 genotype–phenotype mapping or by a simple neural network. Moreover, we consider two different scenarios for the effect of mutations. The same set of strategies is feasible in all four implementations, but the probability that a given strategy arises owing to mutation is largely dependent on the behavioural and genetic architecture. Our individual-based simulations show that this has major implications for the evolutionary outcome. In the ISD, different evolutionarily stable strategies are predominant in the four implementations, while in the IPD each implementation creates a characteristic dynamical pattern. As a consequence, the evolved average level of cooperation is also strongly dependent on the underlying mechanism. We argue that our findings are of general relevance for the evolution of social behaviour, pleading for the integration of a mechanistic perspective in models of social evolution.     

Background context and decision making in hoarding gray jays

If decision makers assign stable fitness-related values to options, preference for the most valuable of simultaneously encounteredoptions should be independent of background context (i.e.,prior options). The tendency to choose optionx versus y shouldbe unaffected by whether the decision maker has already beengiven a choice betweenx' and y' or between x' and y'. Here, food-hoarding gray jays (Perisoreus canadensis) were given aninitial choice between x' (one raisin, 0.5 m into a tube) and y' (three raisins, 0.5 m) or between x' and y' (both identicalto x'). All subjects were then given a choice between x' (oneraisin, 0.3 m) and y' (three raisins, 0.7 m). In violationof the principle of irrelevant alternatives, the "market share"ofx depended on prior options. Subjects initially exposed tocontext {x', y'} showed a stronger preference for x than did subjects initially exposed to {x', y'}, which implies thatthe jays did not assign a fixed value to each option. Subjectsthat initially could obtain a large reward (y') for about thesame "price" (perceived danger) as a small reward (x') apparentlydevalued the large reward (y) in the subsequent choice. Thiseffect may be the joint byproduct of cognitive constraints andan adaptive tendency to use information provided by the context.     

The evolution of matrilineal kinship organization

Matrilineal kinship organization is a human social system that emphasizes interactions between matrilineal kin, i.e. individuals related only through females. The ‘matrilineal puzzle’ refers to the potential for tension characteristic of this social system, owing to the conflict between the interests and responsibilities of men in their roles as brother/uncle versus husband/father. From an evolutionary perspective, matrilineal kinship organization is puzzling when it diverts investment of resources from the individuals who provide the potentially highest reproductive returns. I use a game-theoretic framework to investigate a particular form of matrilineal inheritance—the transfer of property from a maternal uncle to a sororal nephew. The analysis reveals two mechanisms that may make this strategy a stable evolutionary outcome. First, a polygynous male has multiple wives, and hence multiple brothers-in-law; with matrilineal inheritance, each additional brother-in-law may transfer resources to the male''s wife''s offspring, thus potentially contributing to the male''s inclusive fitness. Second, the husband of a polyandrous female is effectively ‘sharing’ paternity with other men; depending on the number of husbands, he may be better off investing in his sister''s offspring. I conclude by discussing how these results address the challenges posed by the occurrence of matrilineal kinship organization.     

Cellular and molecular basis of decision‐making

People think they are in control of their own decisions: what to eat or drink, whom to marry or pick a fight with, where to live, what to buy. Behavioural economists and neurophysiologists have long studied decision‐making behaviours. However, these behaviours have only recently been studied through the light of molecular genetics. Here, we review recent research in mice, Drosophila melanogaster and Caenorhabditis elegans, that analyses the molecular and cellular mechanisms underlying decision‐making. These studies interrogate decision‐making about food, sexual behaviour, aggression or foraging strategies, and add molecular and cell biology understanding onto the consilience of brain and decision.     

How chimpanzees solve collective action problems

We presented small groups of chimpanzees with two collective action situations, in which action was necessary for reward but there was a disincentive for individuals to act owing to the possibility of free-riding on the efforts of others. We found that in simpler scenarios (experiment 1) in which group size was small, there was a positive relationship between rank and action with more dominant individuals volunteering to act more often, particularly when the reward was less dispersed. Social tolerance also seemed to mediate action whereby higher tolerance levels within a group resulted in individuals of lower ranks sometimes acting and appropriating more of the reward. In more complex scenarios, when group size was larger and cooperation was necessary (experiment 2), overcoming the problem was more challenging. There was highly significant variability in the action rates of different individuals as well as between dyads, suggesting success was more greatly influenced by the individual personalities and personal relationships present in the group.