Dynamics of hierarchy formation: the sequential development of dominance relationships
TL;DR: In this article, a method for investigating the behavioral sequences used in forming dominance hierarchies is presented, and the results suggest that hierarchy formation can be best viewed as a developmental process where preceding dominance interactions influence succeeding ones.
Abstract: A method for investigating the behavioral sequences used in forming dominance hierarchies is presented. There are four possible sequences for the formation of the first two dominance relationships in groups of three individuals (triads). Designating the winner in the first relationship formed as the initial dominant, the loser as the initial subordinate, and the animal not involved as the bystander, the four possible sequences are: (1) the initial dominants goes on to dominate the bystander (Double Dominance), (2) the bystander later dominates the initial subordinate (Double Subordinance), (3) the bystander later dominates the initial dominant (Bystander Dominates Initial Dominant), and (4) the initial subordinate later dominates the bystander (Initial Subordinate Dominates Bystander). Although each sequence has an equal probability of occurrence if dominance relationships are formed randomly, two of the sequences have different implications for the formation of the empirically common linear and near linear hierarchies than the other two. Linear and near linear hierarchies are, by definition, composed of all or nearly all triads with transitive dominance relationships (A dominates B, B dominates C, and A dominates C), while hierarchies far from linearity have many triads with intransitive relationships (A dominates B, B dominates C, and C dominates A). Double Dominance and Double Subordinance sequences guarantee the formation of triads with transitive dominance relationships, but the other two sequences can give triads with either transitive or intransitive relationships. Linear and near lincar hierarchies are ensured, therefore, by a preponderance of Double Dominance and Double Subordinance sequences in the component triads of larger groups. In an application of the method developed, sequences of dominance relationships formed in groups of three and four chickens were analyzed. In both experiments Double Dominance and Double Subordinance composed the overwhelming majority of all sequences - 91 % in triads and 87 % in tetrads. A further set of results indicated that intransitive relationships were common in "constructed" triads where chickens met only as component pairs and not in "real" triads where all three met together at the same time. These results suggest that hierarchy formation can be best viewed as a developmental process where preceding dominance interactions influence succeeding ones. This view was characterized as the "jigsaw puzzle" model of hierarchy formation, and it was contrasted with the more classical approach of explaining hierarchy structures by differences in the individual characteristics of group members. Many species beside chickens form linear and near linear hierarchies, and it was hypothesized that Double Dominance and Double Subordinance sequences also compose the majority of sequence occurrences in many of these species. The data available for other species were reviewed and offered tentative support for the hypothesis.
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TL;DR: In this article, a wide list of topics ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading are reviewed and connections between these problems and other, more traditional, topics of statistical physics are highlighted.
Abstract: Statistical physics has proven to be a fruitful framework to describe phenomena outside the realm of traditional physics. Recent years have witnessed an attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. A wide list of topics are reviewed ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading. The connections between these problems and other, more traditional, topics of statistical physics are highlighted. Comparison of model results with empirical data from social systems are also emphasized.
3,840 citations
TL;DR: The chapter presents the interaction dynamics among individuals result in the formation, internal structuring, and collective behaviors of vertebrate groups, and concludes that to understand collective behaviors fully, these properties cannot necessarily be considered in isolation.
Abstract: Publisher Summary The chapter discusses an emerging area of study: that of applying self-organization theory to mobile vertebrate groups composed of many interacting individuals such as bird flocks, ungulate herds, fish schools, and human crowds in an attempt to improve our understanding of underlying organizational principles. Mathematical modeling is becoming increasingly recognized as an important research tool when studying collective behavior. The chapter presents the interaction dynamics among individuals result in the formation, internal structuring, and collective behaviors of vertebrate groups. The chapter explores the distribution of grouping individuals over larger spatial and temporal scales, and discusses how individual behaviors lead to population-level dynamics. Behavioral differences among individuals within a group may have an important internal structuring influence. By using simulation models, it can be shown how individuals can modify their positions relative to other group members without necessitating information about their current position within the group. In considering self-organization within vertebrate groups it is evident that the organization at one level, for example, that of the group relates to that at higher levels. For example, self-sorting processes that lead to internal structuring within groups also result in population-level patterns when such groups fragment, thus affecting the probability that an individual will be in a group of a given size and composition at any moment in time. These population properties then feed back to the individual interactions by changing the probability of encounters among different members of a population. The chapter concludes that to understand collective behaviors fully, these properties cannot necessarily be considered in isolation.
836 citations
Cites background from "Dynamics of hierarchy formation: th..."
...Such effects have been reported in real animal groups (Ginsburg and Allee, 1975; Chase, 1980, 1982a,b, 1985; Francis, 1983; Beaugrand and Zayan, 1984)....
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...Simplistically, such a mechanism assumes that winners of interactions increase their probability of winning future interactions, whereas losers increase their future probability of losing (Chase, 1982a,b)....
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TL;DR: The voluminous, but somewhat disconnected, literature on the neuroendocrine mechanisms that mediate experience effects is reviewed, providing a comprehensive view of how these mechanisms are integrated into overt behaviour.
Abstract: Experience in aggressive contests often affects behaviour during, and the outcome of, later contests. This review discusses evidence for, variations in, and consequences of such effects. Generally, prior winning experiences increase, and prior losing experiences decrease, the probability of winning in later contests, reflecting modifications of expected fighting ability. We examine differences in the methodologies used to study experience effects, and the relative importance and persistence of winning and losing experiences within and across taxa. We review the voluminous, but somewhat disconnected, literature on the neuroendocrine mechanisms that mediate experience effects. Most studies focus on only one of a number of possible mechanisms without providing a comprehensive view of how these mechanisms are integrated into overt behaviour. More carefully controlled work on the mechanisms underlying experience effects is needed before firm conclusions can be drawn.
Behavioural changes during contests that relate to prior experience fall into two general categories. Losing experiences decrease willingness to engage in a contest while winning experiences increase willingness to escalate a contest. As expected from the sequential assessment model of contest behaviour, experiences become less important to outcomes of contests that escalate to physical fighting.
A limited number of studies indicate that integration of multiple experiences can influence current contest behaviour. Details of multiple experience integration for any species are virtually unknown. We propose a simple additive model for this integration of multiple experiences into an individual's expected fighting ability. The model accounts for different magnitudes of experience effects and the possible decline in experience effects over time.
Predicting contest outcomes based on prior experiences requires an algorithm that translates experience differences into contest outcomes. We propose two general types of model, one based solely on individual differences in integrated multiple experiences and the other based on the probability contests reach the escalated phase. The difference models include four algorithms reflecting possible decision rules that convert the perceived fighting abilities of two rivals into their probabilities of winning. The second type of algorithm focuses on how experience influences the probability that a subsequent contest will escalate and the fact that escalated contests may not be influenced by prior experience. Neither type of algorithm has been systematically investigated.
Finally, we review models for the formation of dominance hierarchies that assume that prior experience influences contest outcome. Numerous models have reached varied conclusions depending on which factors examined in this review are included. We know relatively little about the importance of and variation in experience effects in nature and how they influence the dynamics of aggressive interactions in social groups and random assemblages of individuals. Researchers should be very active in this area in the next decade. The role of experience must be integrated with other influences on contest outcome, such as prior residency, to arrive at a more complete picture of variations in contest outcomes. We expect that this integrated view will be important in understanding other types of interactions between individuals, such as mating and predator-prey interactions, that also are affected significantly by prior experiences.
645 citations
Cites background from "Dynamics of hierarchy formation: th..."
...…contest outcome at the dyadic level hence, it is reasonable to assume that such effects could operate during 56 Y. Hsu, R. L. Earley and L. L. Wolf hierarchy establishment (Barnard & Burk, 1979; Chase, 1980, 1982a, b, 1985; Bonabeau, Theraulaz & Deneubourg, 1996; Dugatkin, 1997; Hemelrijk, 2000)....
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01 Jan 1994
TL;DR: A novel formulation of reinforcement learning is proposed that makes behavior selection learnable in noisy, uncertain multi-agent environments with stochastic dynamics, and enables and accelerates learning in complex multi-robot domains.
Abstract: This thesis addresses situated, embodied agents interacting in complex domains. It focuses on two problems: (1) synthesis and analysis of intelligent group behavior, and (2) learning in complex group environments.
Behaviors are proposed as the appropriate level for control and learning. Basic behaviors are introduced as building blocks for synthesizing and analyzing system behavior. The thesis describes the process of selecting such basic behaviors, formally specifying them, algorithmically implementing them, and empirically evaluating them. All of the proposed ideas are validated with a group of up to 20 mobile robots using a basic behavior set consisting of: avoidance, following, aggregation, dispersion, and homing. The set of basic behaviors acts as a substrate for achieving more complex high-level goals and tasks. Two behavior combination operators are introduced, and verified by combining subsets of the above basic behavior set to implement collective flocking and foraging.
A methodology is introduced for automatically constructing higher-level behaviors by learning to select among the basic behavior set. A novel formulation of reinforcement learning is proposed that makes behavior selection learnable in noisy, uncertain multi-agent environments with stochastic dynamics. It consists of using conditions and behaviors for more robust control and minimized state-spaces, and a reinforcement shaping methodology that enables principled embedding of domain knowledge with two types of shaping functions: heterogeneous reward functions and progress estimators. The methodology outperforms two alternatives when tested on a collection of robots learning to forage. The proposed formulation enables and accelerates learning in complex multi-robot domains. The generality of the approach makes it compatible with the existing reinforcement learning algorithms, allowing it to accelerate learning in a variety of domains and applications.
The presented methodologies and results are aimed at extending our understanding of synthesis, analysis, and learning of group behavior. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
425 citations
TL;DR: The results suggest that dominance hierarchy formation is a much richer and more complex phenomenon than previously thought and the implications for evolutionary biology, the social sciences, and the use of animal models in understanding human social organization are explored.
Abstract: Linear hierarchies, the classical pecking-order structures, are formed readily in both nature and the laboratory in a great range of species including humans. However, the probability of getting linear structures by chance alone is quite low. In this paper we investigate the two hypotheses that are proposed most often to explain linear hierarchies: they are predetermined by differences in the attributes of animals, or they are produced by the dynamics of social interaction, i.e., they are self-organizing. We evaluate these hypotheses using cichlid fish as model animals, and although differences in attributes play a significant part, we find that social interaction is necessary for high proportions of groups with linear hierarchies. Our results suggest that dominance hierarchy formation is a much richer and more complex phenomenon than previously thought, and we explore the implications of these results for evolutionary biology, the social sciences, and the use of animal models in understanding human social organization.
334 citations
References
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01 Jan 1971
TL;DR: In this article, a definitive study of the social structure and symbiotic relationships of termites, social wasps, bees, and ants was conducted. But the authors focused on the relationship between ants and termites.
Abstract: Conducts a definitive study of the social structure and symbiotic relationships of termites, social wasps, bees, and ants.
4,679 citations
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01 Jan 1975
633 citations
"Dynamics of hierarchy formation: th..." refers background in this paper
...…rank in previous hierarchies, weight, seniority, relative maturity, and aggressiveness among a variety of other factors (see ALLEE et al., 1949; BROWN, 1975; COLLIAS, 1943; SCHEIN, 1975; and WILSON, 1975 for general reviews and SAVIN-WILLIAMS, 1977, 1979, 1980 for special attention to…...
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TL;DR: Various aspects of sexual behaviour, particularly the active behaviour of mares in oestrus in seeking out stallions, and changes in stallions' behaviour during the breeding season, are described.
460 citations
TL;DR: In this paper, the dominance probability of a peck-right in a flock of domestic hens is analyzed in the presence of social factors, such as the previous history of dominance, which are not included in the present treatment.
431 citations
01 Jan 1975
TL;DR: This monograph reports on a 14 month study of yellow baboons in the Masai-Amboseli Game Reserve, Kenya, an attempt to determine the relationship between agonistic dominance and reproductive success in male baboons and centered around testing a priority-of-access model of mating behavior.
Abstract: This monograph reports on a 14 month study of yellow baboons (Papio cynocephalus) in the Masai-Amboseli Game Reserve, Kenya. The study was an attempt to determine the relationship between agonistic dominance and reproductive success in male baboons and centered around testing a priority-of-access model of mating behavior. Explicit criteria for determining dominance in baboons are presented and the consistency of dominance relationships through time is analyzed for all classes of individuals. Related data on reproductive cycle length, perineal and behavioral indications of the optimal day for mating, changes in female behavior during estrus, and effects of the presence of estrous females on group organization are also included. This work constitutes the first comprehensive field study of baboon mating systems and social organization and emphasizes the use of systematic behavior sampling techniques in the field and quantitative models in the study of primate social behavior.
365 citations
"Dynamics of hierarchy formation: th..." refers background in this paper
...…(TORDOFF, 1954), coyotes (BEKOFF, 1976), cows (SCHEIN & FOHRMAN, 1955), ponies (TYLER, 1972), pigs (RASMUSSEN et al, 1962), rhesus monkeys (SALE, 1967), baboons (HAUSFATER, 1975), vervets (STRUHSAKER, 1967) and human children and adolescents (MISSAKIAN, 1976; SAVIN-WILLIAMS, 1977, 1979, 1980)....
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...Linear and near linear hierarchies are reported in small groups for a broad variety of species including wasps and bumble bees (WILSON, 1971), chaffinches (MARLER, 1955), red cross bills (TORDOFF, 1954), coyotes (BEKOFF, 1976), cows (SCHEIN & FOHRMAN, 1955), ponies (TYLER, 1972), pigs (RASMUSSEN et al, 1962), rhesus monkeys (SALE, 1967), baboons (HAUSFATER, 1975), vervets (STRUHSAKER, 1967) and human children and adolescents (MISSAKIAN, 1976; SAVIN-WILLIAMS, 1977, 1979, 1980)....
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