Evolution Of Collective Behavior Research Articles

Evolutionary dynamics in financial markets with heterogeneities in investment strategies and reference points.

In nature and human societies, the effects of homogeneous and heterogeneous characteristics on the evolution of collective behaviors are quite different from each other. By incorporating pair pattern strategies and reference point strategies into an agent-based model, we have investigated the effects of homogeneous and heterogeneous investment strategies and reference points on price movement. In the market flooded with the investors with homogeneous investment strategies or homogeneous reference points, large price fluctuations occur. In the market flooded with the investors with heterogeneous investment strategies or heterogeneous reference points, moderate price fluctuations occur. The coexistence of different kinds of investment strategies can not only refrain from the occurrence of large price fluctuations but also the occurrence of no-trading states. The present model reveals that the coexistence of heterogeneous populations, whether they are the individuals with heterogeneous investment strategies or heterogeneous reference points of stock prices, is an important factor for the stability of the stock market.

Molecular patterns and processes in evolving sociality: lessons from insects.

Social insects have provided some of the clearest insights into the origins and evolution of collective behaviour. Over 20 years ago, Maynard Smith and Szathmáry defined the most complex form of insect social behaviour-superorganismality-among the eight major transitions in evolution that explain the emergence of biological complexity. However, the mechanistic processes underlying the transition from solitary life to superorganismal living in insects remain rather elusive. An overlooked question is whether this major transition arose via incremental or step-wise modes of evolution. We suggest that examination of the molecular processes underpinning different levels of social complexity represented across the major transition from solitary to complex sociality can help address this question. We present a framework for using molecular data to assess to what extent the mechanistic processes that take place in the major transition to complex sociality and superorganismality involve nonlinear (implying step-wise evolution) or linear (implying incremental evolution) changes in the underlying molecular mechanisms. We assess the evidence for these two modes using data from social insects and discuss how this framework can be used to test the generality of molecular patterns and processes across other major transitions. This article is part of a discussion meeting issue 'Collective behaviour through time'.

Spatial allocation without spatial recruitment in bumblebees

AbstractAny foraging animal is expected to allocate its efforts among resource patches that vary in quality across time and space. For social insects, this problem is shifted to the colony level: the task of allocating foraging workers to the best patches currently available. To deal with this task, honeybees rely upon differential recruitment via the dance language, while some ants use differential recruitment on odor trails. Bumblebees, close relatives of honeybees, should also benefit from optimizing spatial allocation but lack any targeted recruitment system. How bumblebees solve this problem is thus of immense interest to evolutionary biologists studying collective behavior. It has been thought that bumblebees could solve the spatial allocation problem by relying on the summed individual decisions of foragers, who occasionally sample and shift to alternative resources. We use field experiments to test the hypothesis that bumblebees augment individual exploration with social information. Specifically, we provide behavioral evidence that, when higher-concentration sucrose arrives at the nest, employed foragers abandon their patches to begin searching for the better option; they are more likely to accept novel resources if they match the quality of the sucrose solution experienced in the nest. We explored this strategy further by building an agent-based model of bumblebee foraging. This model supports the hypothesis that using social information to inform search decisions is advantageous over individual search alone. Our results show that bumblebees use a collective foraging strategy built on social modulation of individual decisions, providing further insight into the evolution of collective behavior.

Evolution of Collective Behavior in Economic and Management Systems: Stability and Diversity

Evolution of Collective Behavior in Economic and Management Systems: Stability and Diversity

Why Do Hens Pile? Hypothesizing the Causes and Consequences.

Piling is a behavior in laying hens whereby individuals aggregate in larger densities than would be normally expected. When piling behavior leads to mortalities it is known as smothering and its frequent but unpredictable occurrence is a major concern for many egg producers. There are generally considered to be three types of piling: panic, nest box and recurring piling. Whilst nest box and panic piling have apparent triggers, recurring piling does not, making it an enigmatic and ethologically intriguing behavior. The repetitive nature of recurring piling may result in a higher incidence of smothering and could have unconsidered, sub-lethal consequences. Here, we consider the possible causes of recurring piling from an ethological perspective and outline the potential welfare and production consequences. Drawing on a wide range of literature, we consider different timescales of causes from immediate triggers to ontogeny and domestication processes, and finally consider the evolution of collective behavior. By considering different timescales of influence, we built four hypotheses relevant to the causes of piling, which state that the behavior: (i) is caused by hens moving toward or away from an attractant/repellent; (ii) is socially influenced; (iii) is influenced by early life experiences and; (iv) can be described as a maladaptive collective behavior. We further propose that the following could be welfare consequences of piling behavior: Heat stress, physical injury (such as keel bone damage), and behavioral and physiological stress effects. Production consequences include direct and indirect mortality (smothering and knock-on effects of piling, respectively), potential negative impacts on egg quality and on worker welfare. In future studies the causes of piling and smothering should be considered according to the different timescales on which causes might occur. Here, both epidemiological and modeling approaches could support further study of piling behavior, where empirical studies can be challenging.

Artificial selection for schooling behaviour and its effects on associative learning abilities.

The evolution of collective behaviour has been proposed to have important effects on individual cognitive abilities. Yet, in what way they are related remains enigmatic. In this context, the 'distributed cognition' hypothesis suggests that reliance on other group members relaxes selection for individual cognitive abilities. Here, we tested how cognitive processes respond to evolutionary changes in collective motion using replicate lines of guppies (Poecilia reticulata) artificially selected for the degree of schooling behaviour (group polarization) with >15% difference in schooling propensity. We assessed associative learning in females of these selection lines in a series of cognitive assays: colour associative learning, reversal learning, social associative learning, and individual and collective spatial associative learning. We found that control females were faster than polarization-selected females at fulfilling a learning criterion only in the colour associative learning assay, but they were also less likely to reach a learning criterion in the individual spatial associative learning assay. Hence, although testing several cognitive domains, we found weak support for the distributed cognition hypothesis. We propose that any cognitive implications of selection for collective behaviour lie outside of the cognitive abilities included in food-motivated associative learning for visual and spatial cues.

Fitness trade-offs of group formation and movement by Thomson's gazelles in the Serengeti ecosystem.

Collective behaviours contributing to patterns of group formation and coordinated movement are common across many ecosystems and taxa. Their ubiquity is presumably due to altering interactions between individuals and their predators, resources and physical environment in ways that enhance individual fitness. On the other hand, fitness costs are also often associated with group formation. Modifications to these interactions have the potential to dramatically impact population-level processes, such as trophic interactions or patterns of space use in relation to abiotic environmental variation. In a wide variety of empirical systems and models, collective behaviour has been shown to enhance access to ephemeral patches of resources, reduce the risk of predation and reduce vulnerability to environmental fluctuation. Evolution of collective behaviour should accordingly depend on the advantages of collective behaviour weighed against the costs experienced at the individual level. As an illustrative case study, we consider the potential trade-offs on Malthusian fitness associated with patterns of group formation and movement by migratory Thomson's gazelles in the Serengeti ecosystem.This article is part of the theme issue ‘Collective movement ecology’.

Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question ‘why,’ however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment.

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

A Balanced Mixture of Antagonistic Pressures Promotes the Evolution of Parallel Movement.

A common hypothesis about the origins of collective behaviour suggests that animals might live and move in groups to increase their chances of surviving predator attacks. This hypothesis is supported by several studies that use computational models to simulate natural evolution. These studies, however, either tune an ad-hoc model to ‘reproduce’ collective behaviour, or concentrate on a single type of predation pressure, or infer the emergence of collective behaviour from an increase in prey density. In nature, prey are often targeted by multiple predator species simultaneously and this might have played a pivotal role in the evolution of collective behaviour. We expand on previous research by using an evolutionary rule-based system to simulate the evolution of prey behaviour when prey are subject to multiple simultaneous predation pressures. We analyse the evolved behaviour via prey density, polarization, and angular momentum. Our results suggest that a mixture of antagonistic external pressures that simultaneously steer prey towards grouping and dispersing might be required for prey individuals to evolve dynamic parallel movement.

Cooperation enhanced by indirect reciprocity in spatial prisoner’s dilemma games for social P2P systems

Abstract With the growing interest in social Peer-to-Peer (P2P) applications, relationships of individuals are further exploited to improve the performances of reputation systems. It is an on-going challenge to investigate how spatial reciprocity aids indirect reciprocity in sustaining cooperation in practical P2P environments. This paper describes the construction of an extended prisoner’s dilemma game on square lattice networks with three strategies, i.e., defection, unconditional cooperation, and reciprocal cooperation. Reciprocators discriminate partners according to their reputations based on image scoring, where mistakes in judgment of reputations may occur. The independent structures of interaction and learning neighborhood are discussed, with respect to the situation in which learning environments differ from interaction networks. The simulation results have indicated that the incentive mechanism enhances cooperation better in structured peers than among a well-mixed population. Given the realistic condition of inaccurate reputation scores, defection is still successfully held down when the players interact and learn within the unified neighborhoods. Extensive simulations have further confirmed the positive impact of spatial structure on cooperation with different sizes of lattice neighborhoods. And similar conclusions can also be drawn on regular random networks and scale-free networks. Moreover, for the separated structures of the neighborhoods, the interaction network has a critical effect on the evolution dynamics of cooperation and learning environments only have weaker impacts on the process. Our findings further provide some insights concerning the evolution of collective behaviors in social systems.

The Evolution of Collective Behavior: A Dramaturgical Presentation

The Evolution of Collective Behavior: A Dramaturgical Presentation

Self-organization and phase transition in financial markets with multiple choices

Market confidence is essential for successful investing. By incorporating multi-market into the evolutionary minority game, we investigate the effects of investor beliefs on the evolution of collective behaviors and asset prices. It is found that the roles of market confidence are closely related to whether or not there exists another market. When there exists another investment opportunity, different market confidence may lead to the same price fluctuations and the same investment attainment. There are two feedback effects. Being overly optimistic about a particular asset makes an investor become insensitive to losses. A delayed strategy adjustment leads to a decline in wealth and one’s runaway from the market. The withdrawal of the agents results in the optimization of the strategy distributions and an increase in wealth. Being overly pessimistic about a particular asset makes an investor over-sensitive to losses. One’s too frequent strategy adjustment leads to a decline in wealth. The withdrawal of the agents results in the improvement of the market environment and an increase in wealth.

Collective Behavior in Mass Incidents: a study of contemporary China

Mass incidents are inevitable in contemporary China and the first thing we should learn is to adopt a correct attitude towards them. Based on the three elements—activity, interaction and sentiment—of collective behaviors in 52 mass incidents in China during 2007–2011, we find that collective behaviors in mass incidents show significant differences in activity, interaction and sentiment. A grade evaluation method is proposed to estimate the evolution of collective behaviors in 52 mass incidents and to classify such behaviors into five grades. Then the influence factors on the three elements are analyzed using multiple linear regression. The regression results demonstrate that the impacts of location, casualties, inner-group relations, group scale and duration on the three elements are very significant. Finally, in the light of the regression results, some implications of collective behavior in mass incidents are proposed for the relevant authorities in responding to mass incidents.

Murmurations

Murmurations

Inferring the structure and dynamics of interactions in schooling fish

Determining individual-level interactions that govern highly coordinated motion in animal groups or cellular aggregates has been a long-standing challenge, central to understanding the mechanisms and evolution of collective behavior. Numerous models have been proposed, many of which display realistic-looking dynamics, but nonetheless rely on untested assumptions about how individuals integrate information to guide movement. Here we infer behavioral rules directly from experimental data. We begin by analyzing trajectories of golden shiners (Notemigonus crysoleucas) swimming in two-fish and three-fish shoals to map the mean effective forces as a function of fish positions and velocities. Speeding and turning responses are dynamically modulated and clearly delineated. Speed regulation is a dominant component of how fish interact, and changes in speed are transmitted to those both behind and ahead. Alignment emerges from attraction and repulsion, and fish tend to copy directional changes made by those ahead. We find no evidence for explicit matching of body orientation. By comparing data from two-fish and three-fish shoals, we challenge the standard assumption, ubiquitous in physics-inspired models of collective behavior, that individual motion results from averaging responses to each neighbor considered separately; three-body interactions make a substantial contribution to fish dynamics. However, pairwise interactions qualitatively capture the correct spatial interaction structure in small groups, and this structure persists in larger groups of 10 and 30 fish. The interactions revealed here may help account for the rapid changes in speed and direction that enable real animal groups to stay cohesive and amplify important social information.

Effects of dynamic response time in an evolving market

Considering the time scales of global information and personal reaction, we study the role of dynamic response time in the evolution of collective behavior in an evolving market. The insensitiveness to the market information makes the population cluster around a kind of extreme behavior, in which they always follow what happened last time, while a sensitive population tends to self-segregate into opposing groups. The average success rate R among all the agents is found to have a nonmonotonic dependence on the time scale parameter q . There exists a critical value below (above) which R decreases (increases) with the rise of q . Theoretical analyses demonstrate that the higher efficiency found in the market with an insensitive population is related to its predictability. In such a predictable market, the agents following current prediction have a higher winning probability than those rejecting it. Analytical calculations are in good agreement with numerical data.

Statistical mechanics of collective behavior: Macro‐sociology

The spatial and temporal evolution of collective behavior in large populations is simulated with a cellular automaton model and predicted with a statistical mechanical analytical theory of macro‐sociological behavior. The numerical cellular automaton simulations show that the type of collective behavior observed in a group depends sensitively on the group's social temperature with consensus more likely at higher temperatures and fragmented pockets of majority and minority opinions at lower temperatures. An analytical derivation using a mean field approximation confirms this behavior and also identifies a critical social temperature (T, ≈ 1) above which organized collective behavior disappears. Using social forces as well as social temperatures, the statistical mechanical theory predicts existing macro‐sociological data on collective behavior.