A simple threshold rule is sufficient to explain sophisticated collective decision-making

Is collective nest site selection in ants influenced by the anchoring effect?

Evolutionary theory predicts that animals make decisions that maximize fitness. If so, they are expected to adhere to principles of rational choice, which a decision-maker must follow to reliably maximize net benefit. For example, evaluation of an option should not be influenced by the quality of other unchosen options. However, humans and other animals are known to evaluate a mediocre option more favorably after encountering poor options than after encountering no options, a phenomenon known as the 'anchoring effect'. Rationality is also expected in the consensus decisions of animal societies, but the anchoring effect has not previously been tested in that context. Here we show that colonies of the rock ant, Temnothorax rugatulus, demonstrate the anchoring effect during nest site selection - colonies moved more readily from a mediocre nest to a good nest when exposed to poor nests than when exposed to mediocre nests. This effect depended on both current conditions and past experience; movement probability was affected only when colonies were exposed to surrounding nests before and during the emigration. The effect was small, reaching statistical significance in only one of two experimental replicates. We discuss possible mechanisms and ultimate explanations for why colonies show this seemingly suboptimal behavior.

Alternative model systems for cognitive variation: eusocial-insect colonies

Understanding the origins and maintenance of cognitive variation in animal populations is central to the study of the evolution of cognition. However, the brain is itself a complex, hierarchical network of heterogeneous components, from diverse cell types to diverse neuropils, each of which may be of limited use to study in isolation or prohibitively challenging to manipulate in situ. Consequently, highly tractable alternative model systems may be valuable tools. Eusocial-insect colonies display emergent cognitive-like properties from relatively simple social interactions between diverse subunits that can be observed and manipulated while operating collectively. Here, we review the individual-scale mechanisms that cause group-level variation in how colonies solve problems analogous to cognitive challenges faced by brains, like decision-making, attention, and search.

The emergence of a collective sensory response threshold in ant colonies

SignificanceIn this study, we ask how ant colonies integrate information about the external environment with internal state parameters to produce adaptive, system-level responses. First, we show that colonies collectively evacuate the nest when the ground temperature becomes too warm. The threshold temperature for this response is a function of colony size, with larger colonies evacuating the nest at higher temperatures. The underlying dynamics can thus be interpreted as a decision-making process that takes both temperature (external environment) and colony size (internal state) into account. Using mathematical modeling, we show that these dynamics can emerge from a balance between local excitatory and global inhibitory forces acting between the ants. Our findings in ants parallel other complex biological systems like neural circuits.

The Power of Population Effect in Temnothorax Ant House-Hunting: A Computational Modeling Approach

The decentralized cognition of animal groups is both a challenging biological problem and a potential basis for bioinspired design. In this study, we investigated the house-hunting algorithm used by emigrating colonies of Temnothorax ants to reach consensus on a new nest. We developed a tractable model that encodes accurate individual behavior rules, and estimated our parameter values by matching simulated behaviors with observed ones on both the individual and group levels. We then used our model to explore a potential, but yet untested, component of the ants' decision algorithm. Specifically, we examined the hypothesis that incorporating site population (the number of adult ants at each potential nest site) into individual perceptions of nest quality can improve emigration performance. Our results showed that attending to site population accelerates emigration and reduces the incidence of split decisions. This result suggests the value of testing empirically whether nest site scouts use site population in this way, in addition to the well-demonstrated quorum rule. We also used our model to make other predictions with varying degrees of empirical support, including the high cognitive capacity of colonies and their rational time investment during decision-making. In addition, we provide a versatile and easy-to-use Python simulator that can be used to explore other hypotheses or make testable predictions. It is our hope that the insights and the modeling tools can inspire further research from both the biology and computer science community.

Noise resistant synchronization and collective rhythm switching in a model of animal group locomotion

Biology is suffused with rhythmic behaviour, and interacting biological oscillators often synchronize their rhythms with one another. Colonies of some ant species are able to synchronize their activity to fall into coherent bursts, but models of this phenomenon have neglected the potential effects of intrinsic noise and interspecific differences in individual-level behaviour. We investigated the individual and collective activity patterns of two Leptothorax ant species. We show that in one species (Leptothorax sp. W), ants converge onto rhythmic cycles of synchronized collective activity with a period of about 20 min. A second species (Leptothorax crassipilis) exhibits more complex collective dynamics, where dominant collective cycle periods range from 16 min to 2.8 h. Recordings that last 35 h reveal that, in both species, the same colony can exhibit multiple oscillation frequencies. We observe that workers of both species can be stimulated by nest-mates to become active after a refractory resting period, but the durations of refractory periods differ between the species and can be highly variable. We model the emergence of synchronized rhythms using an agent-based model informed by our empirical data. This simple model successfully generates synchronized group oscillations despite the addition of noise to ants' refractory periods. We also find that adding noise reduces the likelihood that the model will spontaneously switch between distinct collective cycle frequencies.

No coordination required for resources allocation during colony fission in a social insect? An individual-based model reproduces empirical patterns

Social insects are classic examples of cooperation and coordination. For instance, laboratory studies of colony relocation, or house-hunting, have investigated how workers coordinate their efforts to swiftly move the colony to the best nesting site available while preserving colony integrity, i.e. avoiding a split. However, several studies have shown that, in some other contexts, individuals may use private rather than social information and may act solitarily rather than in a coordinated way. Here, we study resource allocation by a mature ant colony when it reproduces by fissioning into several colonies. This is a very different task than house hunting in that colony fission seeks the split of the colony. We develop a simple individual-based model to test if colony fission and resource allocation may be carried out by workers acting solitarily with no coordination. Our model reproduces well the pattern of allocation observed in nature (number and size of new colonies). This does not show that workers do not communicate nor coordinate. Rather, it suggests that independent decision making may be an important component of the process of resource allocation.

When less is more: Robot swarms adapt better to changes with constrained communication

To effectively perform collective monitoring of dynamic environments, a robot swarm needs to adapt to changes by processing the latest information and discarding outdated beliefs. We show that in a swarm composed of robots relying on local sensing, adaptation is better achieved if the robots have a shorter rather than longer communication range. This result is in contrast with the widespread belief that more communication links always improve the information exchange on a network. We tasked robots with reaching agreement on the best option currently available in their operating environment. We propose a variety of behaviors composed of reactive rules to process environmental and social information. Our study focuses on simple behaviors based on the voter model-a well-known minimal protocol to regulate social interactions-that can be implemented in minimalistic machines. Although different from each other, all behaviors confirm the general result: The ability of the swarm to adapt improves when robots have fewer communication links. The average number of links per robot reduces when the individual communication range or the robot density decreases. The analysis of the swarm dynamics via mean-field models suggests that our results generalize to other systems based on the voter model. Model predictions are confirmed by results of multiagent simulations and experiments with 50 Kilobot robots. Limiting the communication to a local neighborhood is a cheap decentralized solution to allow robot swarms to adapt to previously unknown information that is locally observed by a minority of the robots.

Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing

It is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology effectively detects component faults. The higher order spectral triple correlation technology successfully applied for rolling bearing fault identification. Experimental investigation of the technology has shown, that the technology effectively identifies rolling bearing fault by electrical data processing at very early stage of fault development. Novel technology comparisons via modelling and experiments of the proposed higher order spectral triple correlation technology and the higher order spectra technology show the higher fault identification effectiveness of the proposed technology over the bicoherence technology.

Interactions between worker ants may influence the growth of ant cemeteries

When an ant dies within a nest, a worker ant carries its corpse away from the nest and drops it onto a pile known as an ant cemetery. These ant cemeteries form cluster patterns, and the dynamics of the corpse piles have been studied experimentally. The aim of the present study was to investigate how sensitivity to the presence of nest-mates would influence the corpse-carrying behaviour of ants, and how this would impact the dynamics of corpse pile clustering. This was achieved by developing an agent-based computational model in which simulated ‘ants’ (the agents) carry and drop ‘corpses’, resulting in the growth of the corpse pile. In the model, the probability of an ant dropping a corpse was tuned according to the presence or absence of nest-mates. The pile dynamics of the resulting model showed a partial match with the time series evolution of corpse piles observed with real ants in previous experimental studies. Although the switch of probabilities is a thought experiment, our results suggest that the corpse-carrying behaviour of worker ants might be influenced by interactions with their nest-mates because there is evidence that ant behaviour can be influenced by encounter rates.

Colony size and initial conditions combine to shape colony reunification dynamics

Group cohesion and collective decision-making are important for many social animals, like social insects, whose societies depend on the coordinated action of individuals to complete collective tasks. A useful model for understanding collective, consensus-driven decision-making is the fluid nest selection dynamics of ant colonies. Certain ant species oscillate between occupying multiple nests simultaneously (polydomy) and reuniting at a single location (monodomy), but little is known about how colonies achieve a consensus around these dynamics. To investigate the factors underpinning the splitting-reunification dynamics of ants, we manipulated the availability and quality of nest sites for the ant Temnothorax rugatulus and measured the likelihood and speed of reunification from contrasting starting conditions. We found that pursuing reunification was more likely for smaller colonies, that rates of initial splitting were lower when colonies could coordinate their activity from a central hub, and that diluting colonies among additional sites did not impair reaching consensus on a single nest. We further found mixed support for a specific threshold of social density that prevents reunification (i.e., prolonged polydomy) and no evidence that nest quality influences reunification behavior. Together our data reveal that consensus driven decisions can be influenced by both external and intrinsic group-level factors and are in no way simple stereotyped processes.

Decision-Making Processes Underlying Pedestrian Behaviors at Signalized Crossing: Part 1. The First to Step off the Kerb

Pedestrians are ideal subjects for the study of decision-making, due to the inter-individual variation in risk taking. Many studies have attempted to understand which environmental factors influence the number of times pedestrians broke the rules at road-crossings, very few focused on the decision-making process of pedestrians according to the different conditions of these variables, that is to say their perception and interpretation of the information they receive. We used survival analyses and modeling to highlight the decision-making process of pedestrians crossing the road at signalized crossings in France and in Japan. For the first pedestrians to step off the kerb, we showed that the probability to cross the road follows three different processes: one at the red signal, one just before the pedestrian signal turns green, and one after the signal has turned green. Globally, the decision of the first pedestrian to cross, whether he or she does so at the green or at the red signal, is influenced by their country of residence. We identify the use of cognitive processes such as risk sensitivity and temporal discounting, and propose new concepts based on the results of this study to decrease the incidence of rule-breaking by pedestrians.

Positive and negative incentive contrasts lead to relative value perception in ants

Humans usually assess things not according to their absolute value, but relative to reference points - a main tenant of Prospect Theory. For example, people rate a new salary relative to previous salaries and salaries of their peers, rather than absolute income. We demonstrate a similar effect in an insect: ants expecting to find low-quality food showed higher acceptance of medium-quality food than ants expecting medium quality, and vice versa for high expectations. Further experiments demonstrate that these contrast effects arise from cognitive rather than mere sensory or pre-cognitive perceptual causes. Social information gained inside the nest can also serve as a reference point: the quality of food received from other ants affected the perceived value of food found later. Value judgement is a key element in decision making, and thus relative value perception strongly influences which option is chosen and ultimately how all animals make decisions.

Parallel vs. comparative evaluation of alternative options by colonies and individuals of the ant Temnothorax rugatulus

Both a single ant and the colony to which it belongs can make decisions, but the underlying mechanisms may differ. Colonies are known to be less susceptible than lone ants to “choice overload”, whereby decision quality deteriorates with increasing number of options. We probed the basis of this difference, using the model system of nest-site selection by the ant Temnothorax rugatulus. We tested the applicability of two competing models originally developed to explain information-processing mechanisms in vertebrates. The Tug of War model states that concurrent alternatives are directly compared, so that choosing between two alternatives takes longer than accepting a single one. In contrast, the Sequential Choice Model assumes that options are examined in parallel, and action takes place once any option reaches a decision criterion, so that adding more options shortens time to act. We found that single ants matched the Tug of War model while colonies fitted the Sequential Choice model. Our study shows that algorithmic models for decision-making can serve to investigate vastly different domains, from vertebrate individuals to both individuals and colonies of social insects.

An agent-based model of nest-site selection in a mass-recruiting ant

Complex systems are modular entities which can collectively generate sophisticated emergent solutions through interactions based on simple, local rules. In this study, I use an agent-based model to elucidate how numerous individual-level components contribute to the collective decision process during house-hunting in a mass-recruiting ant species. Myrmecina nipponica combines the use of pheromone trails with a quorum decision rule in collective decisions among nest sites when searching for a new home. The model employed only individual-level rules but accurately emulated group-level properties observed in empirical studies. Simulations suggest that in this system i) both social and private information are necessary for effective decision making, ii) decision making was effective even with very low numbers of 'discriminating' individuals, iii) individual acceptance thresholds were more influential than quorum thresholds in tuning decisions to emphasise speed or accuracy, and iv) acceptance thresholds could also help tune decisions to suit environmental complexity. Similar findings in species using one-to-one recruitment suggest that some individual parameters, such as acceptance thresholds, may hold key functions in collective decision making regardless of the form of recruitment.

Psychophysical Laws and the Superorganism

Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this study, we show how colony decision time increases with the number of available nests, in agreement with the Hick-Hyman law of psychophysics, and decreases with mean nest quality, in agreement with Piéron’s law. We also show that colony error rate depends on mean nest quality, and difference in quality, in agreement with Weber’s law. Psychophysical laws, particularly Weber’s law, have been found in diverse species, including unicellular organisms. Our theoretical results predict that superorganisms may also exhibit such behaviour, suggesting that these laws arise from fundamental mechanisms of information processing and decision-making. Finally, we propose a combined psychophysical law which unifies Hick-Hyman’s law and Piéron’s law, traditionally studied independently; this unified law makes predictions that can be empirically tested.

Individual crop loads provide local control for collective food intake in ant colonies

Nutritional regulation by ants emerges from a distributed process: food is collected by a small fraction of workers, stored within the crops of individuals, and spread via local ant-to-ant interactions. The precise individual-level underpinnings of this collective regulation have remained unclear mainly due to difficulties in measuring food within ants' crops. Here we image fluorescent liquid food in individually tagged Camponotus sanctus ants and track the real-time food flow from foragers to their gradually satiating colonies. We show how the feedback between colony satiation level and food inflow is mediated by individual crop loads; specifically, the crop loads of recipient ants control food flow rates, while those of foragers regulate the frequency of foraging-trips. Interestingly, these effects do not rise from pure physical limitations of crop capacity. Our findings suggest that the emergence of food intake regulation does not require individual foragers to assess the global state of the colony.

Variability in individual assessment behaviour and its implications for collective decision-making

Self-organized systems of collective behaviour have been demonstrated in a number of group-living organisms. There is, however, less research relating to how variation in individual assessments may facilitate group decision-making. Here, we investigate this using the decentralized system of collective nest choice behaviour employed by the ant Temnothorax albipennis, combining experimental results with computational modelling. In experiments, isolated workers of this species were allowed to investigate new nest sites of differing quality, and it was found that for any given nest quality, there was wide variation among individuals in the durations that they spent within each nest site. Additionally, individual workers were consistent in spending more time in nest sites of higher quality, and less time in those of lower quality. Hence, the time spent in a new nest site must have included an assessment of nest quality. As nest site visit durations (henceforth termed assessment durations) are linked to recruitment, it is possible that the variability we observed may influence the collective decision-making process of colonies. Thus, we explored this further using a computational model of nest site selection, and found that heterogeneous nest assessments conferred a number of potential benefits. Furthermore, our experiments showed that nest quality assessments were flexible, being influenced by experience of prior options. Our findings help to elucidate the potential mechanisms underlying group behaviour, and highlight the importance of heterogeneity among individuals, rather than precise calibration, in shaping collective decision-making.

Ant Droplet Dynamics Evolve via Individual Decision-Making

The droplets of a set of ants were studied while they constructed a bridge. A droplet is a group of ants derived from a larger group. Several experimental studies have revealed the droplet dynamics of ants that resemble the self-organising characteristics that are displayed in their physico-chemical systems. However, little is known regarding how these typical behaviours emerge from individual decision-making. In this study, I developed an agent-based model where artificial ants aggregated, thereby resulting in chain and droplet growth. In my proposed model, the agents tuned their weight thresholds according to the local pattern stability and propagation of negative information. As a result, it was revealed that the droplet dynamics of my proposed model partly matched the time series of droplets of real ants, as demonstrated in previous experimental studies that included the fluctuation function and interdrop increments that followed a scale-free distribution.

Nature of collective decision-making by simple yes/no decision units

The study of collective decision-making spans various fields such as brain and behavioural sciences, economics, management sciences, and artificial intelligence. Despite these interdisciplinary applications, little is known regarding how a group of simple ‘yes/no’ units, such as neurons in the brain, can select the best option among multiple options. One prerequisite for achieving such correct choices by the brain is correct evaluation of relative option quality, which enables a collective decision maker to efficiently choose the best option. Here, we applied a sensory discrimination mechanism using yes/no units with differential thresholds to a model for making a collective choice among multiple options. The performance corresponding to the correct choice was shown to be affected by various parameters. High performance can be achieved by tuning the threshold distribution with the options’ quality distribution. The number of yes/no units allocated to each option and its variability profoundly affects performance. When this variability is large, a quorum decision becomes superior to a majority decision under some conditions. The general features of this collective decision-making by a group of simple yes/no units revealed in this study suggest that this mechanism may be useful in applications across various fields.

Individual versus collective cognition in social insects

The concerted responses of eusocial insects to environmental stimuli are often referred to as collective cognition at the level of the colony. To achieve collective cognition, a group can draw on two different sources: individual cognition and the connectivity between individuals. Computation in neural networks, for example, is attributed more to sophisticated communication schemes than to the complexity of individual neurons. The case of social insects, however, can be expected to differ. This is because individual insects are cognitively capable units that are often able to process information that is directly relevant at the level of the colony. Furthermore, involved communication patterns seem difficult to implement in a group of insects as they lack a clear network structure. This review discusses links between the cognition of an individual insect and that of the colony. We provide examples for collective cognition whose sources span the full spectrum between amplification of individual insect cognition and emergent group-level processes.

Model of the best-of-N nest-site selection process in honeybees

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Response threshold variance as a basis of collective rationality

Determining the optimal choice among multiple options is necessary in various situations, and the collective rationality of groups has recently become a major topic of interest. Social insects are thought to make such optimal choices by collecting individuals' responses relating to an option's value (=a quality-graded response). However, this behaviour cannot explain the collective rationality of brains because neurons can make only 'yes/no' responses on the basis of the response threshold. Here, we elucidate the basic mechanism underlying the collective rationality of such simple units and show that an ant species uses this mechanism. A larger number of units respond 'yes' to the best option available to a collective decision-maker using only the yes/no mechanism; thus, the best option is always selected by majority decision. Colonies of the ant Myrmica kotokui preferred the better option in a binary choice experiment. The preference of a colony was demonstrated by the workers, which exhibited variable thresholds between two options' qualities. Our results demonstrate how a collective decision-maker comprising simple yes/no judgement units achieves collective rationality without using quality-graded responses. This mechanism has broad applicability to collective decision-making in brain neurons, swarm robotics and human societies.

Sensitivity of density-dependent threshold to species composition in arthropod aggregates

How mixed-species groups perform collective behaviours provides unique insights into the mechanisms that drive social interactions. Herein, we followed the aggregation process of two isopod species under monospecific and heterospecific conditions at three population densities. Our experimental results show that the formation of both the monospecific and heterospecific groups responds to a similar threshold function. Furthermore, the two species contribute equally to the mixed-species aggregate growth and are not spatiotemporally segregated. However, we show that the cohesion is weaker and the probability of forming aggregations is lower in heterospecific groups than in monospecific populations. Thus, our results show that amplification processes are shared between species, but that the weighting given to conspecific and heterospecific information differs. We develop a theoretical model to test this hypothesis. The model reproduces our experimental data and shows that a relatively low level of inter-attractions between species is able to generate mixed-species aggregates. Moreover the greater the total population, the lower this parameter value is needed to observe aggregation in both species. This highlights the importance to study not only qualitatively but also quantitatively the heterospecific interactions in mixed-species groups. Finally, the patterns observed could be biologically relevant in favouring the association between species.

Exploration adjustment by ant colonies

How do animals in groups organize their work? Division of labour, i.e. the process by which individuals within a group choose which tasks to perform, has been extensively studied in social insects. Variability among individuals within a colony seems to underpin both the decision over which tasks to perform and the amount of effort to invest in a task. Studies have focused mainly on discrete tasks, i.e. tasks with a recognizable end. Here, we study the distribution of effort in nest seeking, in the absence of new nest sites. Hence, this task is open-ended and individuals have to decide when to stop searching, even though the task has not been completed. We show that collective search effort declines when colonies inhabit better homes, as a consequence of a reduction in the number of bouts (exploratory events). Furthermore, we show an increase in bout exploration time and a decrease in bout instantaneous speed for colonies inhabiting better homes. The effect of treatment on bout effort is very small; however, we suggest that the organization of work performed within nest searching is achieved both by a process of self-selection of the most hard-working ants and individual effort adjustment.

Emigration speed and the production of sexuals in colonies of the ant Temnothorax crassispinus under high and low levels of disturbance

A nest relocation is costly for social insects, and involves hazards. Emigrations were studied in Temnothorax crassispinus ant colonies, which inhabit ephemeral nest sites, and which frequently change their nests. In a laboratory experiment, ant colonies from one group were forced to change their nest sites 10 times over a ca. 3-month period, whilst colonies from the second group were forced to adopt this practice twice (on the beginning of May, and in the second half of July). Colonies of the ant from both the groups reduced their total emigration duration. However, the duration of the transport phase remained unchanged. In the case of colonies with higher level of disturbance, there was no relation between colony growth rate and energy allocation in sexual individuals, whilst a negative correlation between these parameters was present in group with lower level of disturbance. In colonies with lower level of disturbance, the investment in sexuals was not correlated with the number of workers at the end of the experiment, whereas such a correlation was demonstrated for colonies with higher level of disturbance. The disturbance, and thus necessity of frequent nest relocations, may be perceived by ants as a signal that nest sites are of a lower quality and may contribute to a change in energy allocation.

A Design Pattern for Decentralised Decision Making

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling.

Computational model of collective nest selection by ants with heterogeneous acceptance thresholds

Collective decision-making is a characteristic of societies ranging from ants to humans. The ant Temnothorax albipennis is known to use quorum sensing to collectively decide on a new home; emigration to a new nest site occurs when the number of ants favouring the new site becomes quorate. There are several possible mechanisms by which ant colonies can select the best nest site among alternatives based on a quorum mechanism. In this study, we use computational models to examine the implications of heterogeneous acceptance thresholds across individual ants in collective nest choice behaviour. We take a minimalist approach to develop a differential equation model and a corresponding non-spatial agent-based model. We show, consistent with existing empirical evidence, that heterogeneity in acceptance thresholds is a viable mechanism for efficient nest choice behaviour. In particular, we show that the proposed models show speed-accuracy trade-offs and speed-cohesion trade-offs when we vary the number of scouts or the quorum threshold.

Confidence sharing: an economic strategy for efficient information flows in animal groups

Social animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication.

Cooperative groups are abundant on all scales of the biological world. Despite much empirical evidence on a wide variety of natural communication schemes, there is still a growing need for rigorous tools to quantify and understand the information flows involved. Here, we borrow techniques from information theory and theoretical distributed computing to study information sharing within animal groups. We consider a group of individuals that integrate personal and social information to obtain improved knowledge of their surroundings. We rigorously show that communication between such individuals can be compressed into simple messages that contain an opinion and a corresponding confidence parameter. While this algorithm is extremely efficient, further reduction in communication capacity may greatly hamper collective performances.

Resource redistribution in polydomous ant nest networks: local or global?

An important problem facing organisms in a heterogeneous environment is how to redistribute resources to where they are required. This is particularly complex in social insect societies as resources have to be moved both from the environment into the nest and between individuals within the nest. Polydomous ant colonies are split between multiple spatially separated, but socially connected, nests. Whether, and how, resources are redistributed between nests in polydomous colonies is unknown. We analyzed the nest networks of the facultatively polydomous wood ant Formica lugubris. Our results indicate that resource redistribution in polydomous F. lugubris colonies is organized at the local level between neighboring nests and not at the colony level. We found that internest trails connecting nests that differed more in their amount of foraging were stronger than trails between nests with more equal foraging activity. This indicates that resources are being exchanged directly from nests with a foraging excess to nests that require resources. In contrast, we found no significant relationships between nest properties, such as size and amount of foraging, and network measures such as centrality and connectedness. This indicates an absence of a colony-level resource exchange. This is a clear example of a complex behavior emerging as a result of local interactions between parts of a system.

How collective comparisons emerge without individual comparisons of the options

Collective decisions in animal groups emerge from the actions of individuals who are unlikely to have global information. Comparative assessment of options can be valuable in decision-making. Ant colonies are excellent collective decision-makers, for example when selecting a new nest-site. Here, we test the dependency of this cooperative process on comparisons conducted by individual ants. We presented ant colonies with a choice between new nests: one good and one poor. Using individually radio-tagged ants and an automated system of doors, we manipulated individual-level access to information: ants visiting the good nest were barred from visiting the poor one and vice versa. Thus, no ant could individually compare the available options. Despite this, colonies still emigrated quickly and accurately when comparisons were prevented. Individual-level rules facilitated this behavioural robustness: ants allowed to experience only the poor nest subsequently searched more. Intriguingly, some ants appeared particularly discriminating across emigrations under both treatments, suggesting they had stable, high nest acceptance thresholds. Overall, our results show how a colony of ants, as a cognitive entity, can compare two options that are not both accessible by any individual ant. Our findings illustrate a collective decision process that is robust to differences in individual access to information.

Physical and biological determinants of collective behavioural dynamics in complex systems: pulling chain formation in the nest-weaving ant Oecophylla smaragdina

The evolution of nest weaving, the inclusion of larval silk in the nest walls, is considered one of the pinnacles of cooperative behaviour in social insects. Within the four ant genera in which this has evolved, Oecophylla are unique in being the only group that precedes the deposition of larval silk by actively manipulating the leaf substrate to form a nest chamber. Here we provide the first descriptions of the manipulation process within a complex-systems framework. Substrate manipulation involves individual ants selecting, grasping and attempting to pull the edge of the substrate. These individuals are then joined by nest mates at the work site, who either select a site beside the first individual or grasp the body of the first or preceding worker to form a chain of pulling ants that together drag and bend the substrate. Site selection by individual workers is not random when confronted with an artificial leaf, with individuals more likely to grasp a substrate at its tip rather than along a more broad edge. The activity of additional individuals is also not random, with their activity being grouped in both space and time. Additional individuals are more likely to join an existing biting individual or pulling group. The positive feedback associated with the early stages of pulling behaviour appears typical for many of the collective actions observed in social insects.

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.

The decision to fight or flee - insights into underlying mechanism in crickets

Ritualized fighting between conspecifics is an inherently dangerous behavioral strategy, optimized to secure limited resources at minimal cost and risk. To be adaptive, potential rewards, and costs of aggression must be assessed to decide when it would be more opportune to fight or flee. We summarize insights into the proximate mechanisms underlying this decision-making process in field crickets. As in other animals, cricket aggression is enhanced dramatically by motor activity, winning, and the possession of resources. Pharmacological manipulations provide evidence that these cases of experience dependent enhancement of aggression are each mediated by octopamine, the invertebrate counterpart to adrenaline/noradrenaline. The data suggest that both physical exertion and rewarding aspects of experiences can activate the octopaminergic system, which increases the propensity to fight. Octopamine thus represents the motivational component of aggression in insects. For the decision to flee, animals are thought to assess information from agonistic signals exchanged during fighting. Cricket fights conform to the cumulative assessment model, in that they persist in fighting until the sum of their opponent’s actions accumulates to some threshold at which they withdraw. We discuss evidence that serotonin, nitric oxide, and some neuropeptides may promote an insect’s tendency to flee. We propose that the decision to fight or flee in crickets is controlled simply by relative behavioral thresholds. Rewarding experiences increase the propensity to fight to a level determined by the modulatory action of octopamine. The animal will then flee only when the accumulated sum of the opponent’s actions surpasses this level; serotonin and nitric oxide may be involved in this process. This concept is in line with the roles proposed for noradrenaline, serotonin, and nitric oxide in mammals and suggests that basic mechanisms of aggressive modulation may be conserved in phylogeny.