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Evolution of cooperative turn-taking

Profile image of Andrew M ColmanAndrew M Colman

2016

Abstract

Question: How can the evolution of turn-taking be explained in species without language? Features of model: Using a genetic algorithm incorporating mutation and crossover, we studied noisy decision making in three repeated two-player games in which we predicted on theoretical grounds that cooperative turn-taking would evolve and three games in which we expected synchronized cooperation to evolve. Ranges of key variables: We set population size to 20, number of rounds to be played by each pair in each generation to 200, and number of evolutionary generations to 2000, and we repeated each simulation 10 times to check the stability of the results. Results: Cooperative turn-taking and (unexpectedly) a form of double turn-taking evolved in the alternation games, and joint cooperation evolved in the synchronization games. We propose a mechanism to explain how cooperative turn-taking can evolve mechanically, even without communication or insight, as it did in our simulations.

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Andrew M Colman

A genetic algorithm incorporating mutation and crossing-over was used to investigate the evolution of social behaviour in repeated Prisoner's Dilemma, Chicken (Hawk-Dove), Battle of the Sexes, and Leader games. The results show that the strategic structure of an interaction has a crucial determining effect on the type of social behaviour that evolves. In particular, simulations using repeated Prisoner's Dilemma and Chicken (Hawk-Dove) games lead to the emergence of genes coding for symmetric reciprocity and the evolution of mutual cooperation, whereas simulations using repeated Battle of the Sexes and Leader games lead to near-fixation of genes coding for asymmetric strategic choices and the evolution of coordinated alternating reciprocity. A mechanism is suggested whereby, in games with asymmetric equilibrium points, coordinated alternating reciprocity might evolve without insight or communication between players. r

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Evolution of Cooperation Without Awareness in Minimal Social Situations
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A surprising prediction from a simple evolutionary game-theoretic model, based on meagre assumptions, is that a form of cooperation can evolve among agents acting without any deliberate intention to cooperate. There are circumstances in which agents can learn to behave cooperatively without even becoming aware of their strategic interdependence. This phenomenon occurs in what are called minimal social situations, through an unconscious mechanism of adaptive learning in pairs or groups of agents lacking any deliberate intention to cooperate. 1 Whether or not it is reasonable to interpret this as a form of teamwork is debatable. The argument pivots on what are considered to be the essential or prototypic features of teamwork, and other contributors to this volume are better qualified than I to analyse this conceptual issue. But what seems uncontroversial is that minimal social situations represent special or limiting cases that should interest people who study teamwork and may help to throw light on more complex forms of teamwork. Minimal social situations are curiosities, outside the mainstream of evolutionary game theory, but the underlying theory is intrinsically interesting and may turn out to have some utility in explaining the evolution of social behaviour in conditions of incomplete information. The increasing popularity of evolutionary games, from the closing decades of the second millennium onwards, has been fuelled by a growing suspicion that orthodox game theory, based on ideally rational players, may be irredeemably indeterminate. Orthodox game theory seeks to specify the strategies that would be chosen by rational players -rational in the sense of invariably acting to maximize their expected utilities relative to their knowledge and beliefs. It is easy to prove, via the celebrated Indirect Argument 2 of von Neumann and Morgenstern (1944, pp. 146-8), that if a game has a uniquely rational solution, then that solution necessarily comprises a profile of strategies that we now call a Nash equilibrium in which each strategy is a utility-maximizing best reply to the combined strategies of the remaining players. But most interesting games, apart from those that are strictly competitive (finite, two-person, zero-sum), have multiple Nash equilibria that are neither equivalent nor interchangeable, and this implies that rational players, having identified the equilibria of a game, are left with a problem of equilibrium selection. It is in this sense that classical game theory, based on Nash equilibrium, is indeterminate. Evolutionary game theory came into its own following the partial eclipse of the purely rational and normative approach set out by the founding game theorists. 3 It deals with nonrational strategic interaction driven by mindless adaptive processes based on trial and error. It can be traced to a passage in John Nash's doctoral thesis, completed in 1950 but not published in full until more than half a century later . Evolutionary game models are designed to explore the behaviour of goal-directed automata in simulated strategic interactions (Hofbauer and Sigmund, 1998;. In some models, based on adaptive learning mechanisms, individual automata adjust their strategy choices in response to the payoffs they receive in simulated interactions; in others, based on replicator dynamics, the relative proportions of different types of automata in the population change in response to payoffs. In either case, the interacting automata are programmed to maximize their individual payoffs, even though their strategy choices are made without conscious thought or deliberate choice. Evolutionary models generally converge to the vicinity of evolutionarily stable strategies, 4 which are invulnerable to evolutionary invasion by alternative strategies and (it

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Related topics

  • Evolutionary Game Theory
  • Coordination Game
  • Battle of the Sexes
  • Stag Hunt
  • Tit for Tat
  • Turn Taking
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