Results for 'evolutionary games'

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  1.  30
    Cycles Versus Equilibrium in Evolutionary Games.Thomas W. L. Norman - 2010 - Theory and Decision 69 (2):167-182.
    Mixed-strategy equilibria are typically rather unstable in evolutionary game theory. “Monocyclic” games, such as Rock–Paper–Scissors, have only mixed equilibria, some of which are “stable” in the sense that sequential best replies lead to them; yet, even these games are prone to stable cycles under discrete-time simultaneous best replies, giving an unusual equilibrium-selection problem. This article analyzes such games in a random-utility setting where changing strategies is costly, and the speed of the dynamic is, thus, endogenous. The (...)
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  2. Evolutionary Games in Natural, Social, and Virtual Worlds.Daniel Friedman & Barry Sinervo - 2016 - Oxford University Press USA.
    Over the last 25 years, evolutionary game theory has grown with theoretical contributions from the disciplines of mathematics, economics, computer science and biology. It is now ripe for applications. In this book, Daniel Friedman---an economist trained in mathematics---and Barry Sinervo---a biologist trained in mathematics---offer the first unified account of evolutionary game theory aimed at applied researchers. They show how to use a single set of tools to build useful models for three different worlds: the natural world studied by (...)
     
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  3. Modeling Social and Evolutionary Games.Angela Potochnik - 2012 - Studies in History and Philosophy of Science Part C 43 (1):202-208.
    When game theory was introduced to biology, the components of classic game theory models were replaced with elements more befitting evolutionary phenomena. The actions of intelligent agents are replaced by phenotypic traits; utility is replaced by fitness; rational deliberation is replaced by natural selection. In this paper, I argue that this classic conception of comprehensive reapplication is misleading, for it overemphasizes the discontinuity between human behavior and evolved traits. Explicitly considering the representational roles of evolutionary game theory brings (...)
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  4.  60
    Truth and Probability in Evolutionary Games.Jeffrey A. Barrett - unknown
    This paper concerns two composite Lewis-Skyrms signaling games. Each consists in a base game that evolves a language descriptive of nature and a metagame that coevolves a language descriptive of the base game and its evolving language. The first composite game shows how a pragmatic notion of truth might coevolve with a simple descriptive language. The second shows how a pragmatic notion of probability might similarly coevolve. Each of these pragmatic notions is characterized by the particular game and role (...)
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  5.  40
    Evolutionary Games Without Rationality?Martin Bunzl - 2002 - Philosophy of the Social Sciences 32 (3):365-378.
    It is sometimes claimed that evolutionary game theory provides a basis fordoing without rationality. The author defends the thesis that on any plausibleconstrual of the assumptions underlying evolutionary game theory, it cannotprovide a plausible basis for deviations from rationality. But on any plausibleconstrual of rationality, evolutionary game theory cannot provide an alternativethat coincides with the outcomes dictated by considerations of rationality,either. Key Words: evolutionary game theory • game theory • rationality • Skyrms.
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  6.  24
    In Evolutionary Games, Enlightened Self-Interests Are Still Ultimately Self-Interests.Thomas Getty - 2007 - Behavioral and Brain Sciences 30 (1):25-26.
    Evolutionary theory provides a firm foundation for the unification of the behavioral sciences, and the beliefs, preferences, and constraints (BPC) model is a useful analytical tool for understanding human behavior. However, evolutionary theory suggests that if other-regarding preferences expressed by humans have evolved under selection, they are ultimately, if not purely, in the constrained, relative self-interests of individuals who express them. (Published Online April 27 2007).
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  7.  11
    “Was You Ever Bit by a Dead Bee?” – Evolutionary Games and Dominated Strategies.Karl Sigmund - 2003 - Behavioral and Brain Sciences 26 (2):175-176.
    On top of the puzzles mentioned by Colman comes the puzzle of why rationality has bewitched classical game theory for so long. Not the smallest merit of evolutionary game theory is that it views rationality as a limiting case, at best. But some problems only become more pressing.
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  8.  13
    Evolutionary Games in the Agricultural Product Quality and Safety Information System: A Multiagent Simulation Approach.Xin Su, Shengsen Duan, Shubing Guo & Haolong Liu - 2018 - Complexity 2018:1-13.
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  9.  9
    Corrigendum to “Evolutionary Games in the Agricultural Product Quality and Safety Information System: A Multiagent Simulation Approach”.Xin Su, Shengsen Duan, Shubing Guo & Haolong Liu - 2019 - Complexity 2019:1-1.
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  10. Generic Properties of Evolutionary Games and Adaptationism.Simon M. Huttegger - 2010 - Journal of Philosophy 107 (2):80-102.
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  11.  8
    Evolutionary Games and Morality.Dennis Krebs - 2000 - Journal of Consciousness Studies 7 (1-2):1-2.
    The implications of game theory models of the evolution of strategies of exchange are explored with respect to the evolution of moral dispositions. I argue that dispositions to practice tit for tat strategies could have evolved, but the moral behaviours to which they give rise do not fare well on criteria of morality. Inasmuch as the strategy implicit in the Golden Rule is unconditional, it could not have evolved in environments containing strategies that exploit it. However, dispositions to invoke conditional (...)
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  12. Evolutionary Dynamics of Lewis Signaling Games: Signaling Systems Vs. Partial Pooling.Simon Huttegger, Brian Skyrms, Rory Smead & Kevin Zollman - 2010 - Synthese 172 (1):177-191.
    Transfer of information between senders and receivers, of one kind or another, is essential to all life. David Lewis introduced a game theoretic model of the simplest case, where one sender and one receiver have pure common interest. How hard or easy is it for evolution to achieve information transfer in Lewis signaling?. The answers involve surprising subtleties. We discuss some if these in terms of evolutionary dynamics in both finite and infinite populations, with and without mutation.
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  13.  13
    Population Games and Evolutionary Dynamics.William H. Sandholm - 2010 - MIT Press.
    A systematic, rigorous, comprehensive, and unified overview of evolutionary game theory.
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  14.  5
    A Note on Altruism in Asymmetric Games: An Indirect Evolutionary Approach.Jiabin Wu - 2017 - Biological Theory 12 (3):181-188.
    This article studies the evolution of altruism. We consider a model in which a population of agents are assortatively matched to play some asymmetric two-player game, and evolution operates at the level of behavior rules. We find that the relationship between the evolutionarily stable level of altruism and the index of assortativity of matching is determined by two novel features: whether the total payoff function of the game exhibits complementarity or substitutability; whether the two players’ strategies affect each other’s fitness (...)
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  15.  18
    Individual Differences in Evolutionary Perspective: The Games People Play.Diane S. Berry & Stan A. Kuczaj - 2000 - Behavioral and Brain Sciences 23 (4):592-593.
    The emphasis on individual differences in evolutionary theories is important and has not received adequate attention. Strategic Pluralism makes a major contribution by addressing these issues, but like other evolutionary models (e.g., game theory) does not articulate the specific mechanisms underlying strategy selection. Specification of such mechanisms is an essential next step in the development of these models.
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  16.  30
    Game Theory as Mathematics for Biology: Evolutionary Dynamics and Extensive Form Games Ross Cressman Cambridge, MA: MIT Press, 2003 (330 Pp; $48.00 Hbk; ISBN 0262033054); Moral Sentiments and Material Interests Herbert Gintis , Samuel Bowles , Robert Boyd and Ernst Fehr , Eds Cambridge, MA: MIT Press, 2005 (416 Pp; $50.00 Hbk; ISBN 0262072521).Don Ross - 2007 - Biological Theory 2 (1):104-107.
  17.  11
    Grounding Symbols Through Evolutionary Language Games.Luc Steels - 2002 - In A. Cangelosi & D. Parisi (eds.), Simulating the Evolution of Language. Springer Verlag. pp. 211--226.
  18.  1
    Conventionality and Causality in Lewis-Type Evolutionary Prediction Games.Gordon Michael Purves - forthcoming - British Journal for the Philosophy of Science.
  19. Evolutionary Network Games: Equilibria From Imitation and Best Response Dynamics.Giulio Cimini - 2017 - Complexity 2017:1-14.
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  20.  31
    Stochastic Evolution of Rules for Playing Finite Normal Form Games.Fabrizio Germano - 2007 - Theory and Decision 62 (4):311-333.
    The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the “folk results” of evolutionary game theory, typically obtained with a fixed game and fixed strategies, carry over to the present environments. The results are also related to some recent experiments on rules and games.
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  21.  73
    The Evolution of Coding in Signaling Games.Jeffrey A. Barrett - 2009 - Theory and Decision 67 (2):223-237.
    Signaling games with reinforcement learning have been used to model the evolution of term languages (Lewis 1969, Convention. Cambridge, MA: Harvard University Press; Skyrms 2006, “Signals” Presidential Address. Philosophy of Science Association for PSA). In this article, syntactic games, extensions of David Lewis’s original sender–receiver game, are used to illustrate how a language that exploits available syntactic structure might evolve to code for states of the world. The evolution of a language occurs in the context of available vocabulary (...)
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  22.  30
    Two-Speed Evolution of Strategies and Preferences In Symmetric Games.Alex Possajennikov - 2004 - Theory and Decision 57 (3):227-263.
    Agents in a large population are randomly matched to play a certain game, payoffs in which represent fitness. Agents may have preferences that are different from fitness. They learn strategies according to their preferences, and evolution changes the preference distribution in the population according to fitness. When agents know the preferences of the opponent in a match, only efficient symmetric strategy profiles of the fitness game can be stable. When agents do not know the preferences of the opponent, only Nash (...)
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  23. A Mutualistic Approach to Morality: The Evolution of Fairness by Partner Choice.Nicolas Baumard, Jean-Baptiste André & Dan Sperber - 2013 - Behavioral and Brain Sciences 36 (1):59-122.
    What makes humans moral beings? This question can be understood either as a proximate question or as an ultimate question. The question is about the mental and social mechanisms that produce moral judgments and interactions, and has been investigated by psychologists and social scientists. The question is about the fitness consequences that explain why humans have morality, and has been discussed by evolutionary biologists in the context of the evolution of cooperation. Our goal here is to contribute to a (...)
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  24.  86
    Determining Truth Conditions in Signaling Games.William F. Harms - 2010 - Philosophical Studies 147 (1):23 - 35.
    Evolving signaling systems can be said to induce partitions on the space of world states as they approach equilibrium. Formalizing this claim provides a general framework for understanding what it means for language to “cut nature at its seams”. In order to avoid taking our current best science as providing the adaptive target for all evolving systems, the state space of the world must be characterized exclusively in terms of the coincidence of stimuli and payoffs that drives the evolution of (...)
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  25.  21
    Genetic Learning in Strategic Form Games.Herbert Dawid & Alexander Mehlmann - 1996 - Complexity 1 (5):51-59.
  26.  53
    Learning with Neighbours.Roland Mühlenbernd - 2011 - Synthese 183 (S1):87-109.
    I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays influence his (...)
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  27.  12
    On the Relative Importance of Haplo-Diploidy, Assortative Mating and Social Synergy on the Evolutionary Emergence of Social Behavior.Klaus Jaffe - 2001 - Acta Biotheoretica 49 (1):29-42.
    Advances in multiagent simulation techniques make it possible to study more realistic dynamics of complex systems and allow evolutionary theories to be tested. Here I use simulations to assess the relative importance of reproductive systems (haplodiploidy vs. diploidy), mate selection (assortative mating vs. random mating) and social economics (pay-off matrices of evolutionary games) in the evolutionary dynamics leading to the emergence of social cooperation in the provision of parental care. The simulations confirm that haplo-diploid organisms and (...)
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  28.  26
    The Evolution of Compositionality in Signaling Games.Michael Franke - 2016 - Journal of Logic, Language and Information 25 (3-4):355-377.
    Compositionality is a key design feature of human language: the meaning of complex expressions is, for the most part, systematically constructed from the meanings of its parts and their manner of composition. This paper demonstrates that rudimentary forms of compositional communicative behavior can emerge from a variant of reinforcement learning applied to signaling games. This helps explain how compositionality could have emerged gradually: if unsophisticated agents can evolve prevalent dispositions to communicate compositional-like, there is a direct evolutionary benefit (...)
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  29.  40
    Robustness and Conceptual Analysis in Evolutionary Game Theory.Zachary Ernst - 2005 - Philosophy of Science 72 (5):1187-1196.
    A variety of robustness objections have been made against evolutionary game theory. One of these objections alleges that the games used in the underlying model are too arbitrary and oversimplified to generate a robust model of interesting prosocial behaviors. In this paper, I argue that the robustness objection can be met. However, in order to do so, we must attend to important conceptual issues regarding the nature of fairness, justice, and other moral concepts. Specifically, we must better understand (...)
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  30.  38
    Chaos in Game Dynamics.Brian Skyrms - 1992 - Journal of Logic, Language and Information 1 (2):111-130.
    Two examples demonstrate the possibility of extremely complicated non-convergent behavior in evolutionary game dynamics. For the Taylor-Jonker flow, the stable orbits for three strategies were investigated by Zeeman. Chaos does not occur with three strategies. This papers presents numerical evidence that chaotic dynamics on a strange attractor does occur with four strategies. Thus phenomenon is closely related to known examples of complicated behavior in Lotka-Volterra ecological models.
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  31.  34
    Evolutionary Equilibria: Characterization Theorems and Their Implications. [REVIEW]Jonathan Bendor & Piotr Swistak - 1998 - Theory and Decision 45 (2):99-159.
    To understand the meaning of evolutionary equilibria, it is necessary to comprehend the ramifications of the evolutionary model. For instance, a full appreciation of Axelrod's The Evolution of Cooperation requires that we identify assumptions under which conditionally cooperative strategies, like Tit For Tat, are and are not evolutionarily stable. And more generally, when does stability fail? To resolve these questions we re-examine the very foundations of the evolutionary model. The results of this paper can be analytically separated (...)
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  32.  35
    Effective Choice in All the Symmetric 2 × 2 Games.David Goforth & David Robinson - 2012 - Synthese 187 (2):579-605.
    Solution concepts for game play implicitly assume what information is relevant for choosing moves. Maximin and Eliminating Dominated Strategies use payoff order; mixed strategies and Harsanyi's risk dominance use payoff values. "Cooperative" strategies use previous choices, ignoring payoffs altogether. We first define the 12 symmetric 2 × 2 games as a continuous payoff space then use this space to evaluate strategies based on different types of information. Strategic success is shown to be sensitive to actual payoffs and seldom consistent (...)
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  33.  30
    The Co‐Evolution of Cooperation and Complexity in a Multi‐Player, Local‐Interaction Prisoners' Dilemma.Peter S. Albin & Duncan K. Foley - 2001 - Complexity 6 (3):54-63.
  34.  19
    Chaos and the Explanatory Significance of Equilibrium: Strange Attractors in Evolutionary Game Dynamics.Brian Skyrms - 1992 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1992:374-394.
    This paper discusses the explanatory significance of the equilibrium concept in the context of an example of extremely complicated dynamical behavior. In particular, numerical evidence is presented for the existence of chaotic dynamics on a "strange attractor" in the evolutionary game dynamics introduced by Taylor and Jonker [also known as the "replicator dynamics"]. This phenomenon is present already in four strategy evolutionary games where the dynamics takes place in a simplex in three dimensional space-the lowest number of (...)
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  35.  18
    Vagueness and Imprecise Imitation in Signalling Games.Michael Franke & José Pedro Correia - 2018 - British Journal for the Philosophy of Science 69 (4):1037-1067.
    Signalling games are popular models for studying the evolution of meaning, but typical approaches do not incorporate vagueness as a feature of successful signalling. Complementing recent like-minded models, we describe an aggregate population-level dynamic that describes a process of imitation of successful behaviour under imprecise perception and realization of similar stimuli. Applying this new dynamic to a generalization of Lewis’s signalling games, we show that stochastic imprecision leads to vague, yet by-and-large efficient signal use, and, moreover, that it (...)
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  36.  54
    Evolutionary Explanations of Indicatives and Imperatives.Simon M. Huttegger - 2007 - Erkenntnis 66 (3):409-436.
    Recently there has been some interest in studying the explanation of meaning by using signaling games. I shall argue that the meaning of signals in signaling games remains sufficiently unclear to motivate further investigation. In particular, the possibility of distinguishing imperatives and indicatives at a fundamental level will be explored. Thereby I am trying to preserve the generality of the signaling games framework while bringing it closer to human languages. A number of convergence results for the (...) dynamics of our models will be proved. (shrink)
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  37.  15
    Games and Kinds.Cailin O’Connor - 2016 - British Journal for the Philosophy of Science:axx027.
    In response to those who argue for ‘property cluster’ views of natural kinds, I use evolutionary models of sim-max games to assess the claim that linguistic terms will appropriately track sets of objects that cluster in property spaces. As I show, there are two sorts of ways this can fail to happen. First, evolved terms that do respect property structure in some senses can be conventional nonetheless. Second, and more crucially, because the function of linguistic terms is to (...)
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  38. Signalling Games Select Horn Strategies.Robert van Rooy - 2004 - Linguistics and Philosophy 27 (4):493-527.
    In this paper I will discuss why (un) marked expressionstypically get an (un)marked interpretation: Horn''sdivision of pragmatic labor. It is argued that it is aconventional fact that we use language this way.This convention will be explained in terms ofthe equilibria of signalling games introduced byLewis (1969), but now in an evolutionary setting. Iwill also relate this signalling game analysis withParikh''s (1991, 2000, 2001) game-theoretical analysis ofsuccessful communication, which in turn is compared withBlutner''s: 2000) bi-directional optimality theory.
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  39.  26
    The Evolution of Simple Rule-Following.Jeffrey A. Barrett - 2013 - Biological Theory 8 (2):142-150.
    We are concerned here with explaining how successful rule-following behavior might evolve and how an old evolved rule might come to be successfully used in a new context. Such rule-following behavior is illustrated in the transitive judgments of pinyon and scrub-jays (Bond et al., Anim Behav 65:479–487, 2003). We begin by considering how successful transitive rule-following behavior might evolve in the context of Skyrms–Lewis sender–receiver games (Lewis, Convention. Harvard University Press, Cambridge, 1969; Skyrms, Philos Sci 75:489–500, 2006). We then (...)
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  40.  28
    Conventional Semantic Meaning in Signalling Games with Conflicting Interests.Elliott O. Wagner - 2015 - British Journal for the Philosophy of Science 66 (4):751-773.
    Lewis signalling games are often used to explain how it is possible for simple agents to develop systems of conventional semantic meaning. In these games, all players obtain identical payoffs in every outcome. This is an unrealistic payoff structure, but it is often employed because it is thought that semantic meaning will not emerge if interests conflict. Here it is shown that not only is conventional meaning possible when interests conflict, but it is the most likely outcome in (...)
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  41.  87
    The Flow of Information in Signaling Games.Brian Skyrms - 2010 - Philosophical Studies 147 (1):155 - 165.
    Both the quantity of information and the informational content of a signal are defined in the context of signaling games. Informational content is a generalization of standard philosophical notions of propositional content. It is shown how signals that initially carry no information may spontaneously acquire informational content by evolutionary or learning dynamics. It is shown how information can flow through signaling chains or signaling networks.
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  42.  40
    Evolutionary Considerations in the Framing of Social Norms.B. Skyrms & K. J. S. Zollman - 2010 - Politics, Philosophy and Economics 9 (3):265-273.
    In this article, we aim to illustrate evolutionary explanations for the emergence of framing effects, discussed in detail in Cristina Bicchieri’s The Grammar of Society . We show how framing effects might evolve which coalesce two economically distinct interactions into a single one, leading to apparently irrational behavior in each individual interaction. Here we consider the now well-known example of the ultimatum game, and show how this ‘irrational’ behavior might result from a single norm which governs behavior in multiple (...)
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  43.  46
    An Evolutionary Perspective on the Long-Term Efficiency of Costly Punishment.Ulrich J. Frey & Hannes Rusch - 2012 - Biology and Philosophy 27 (6):811-831.
    Many studies show that punishment, although able to stabilize cooperation at high levels, destroys gains which makes it less efficient than alternatives with no punishment. Standard public goods games (PGGs) in fact show exactly these patterns. However, both evolutionary theory and real world institutions give reason to expect institutions with punishment to be more efficient, particularly in the long run. Long-term cooperative partnerships with punishment threats for non-cooperation should outperform defection prone non-punishing ones. This article demonstrates that fieldwork (...)
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  44.  43
    Robustness in Signaling Games.Simon M. Huttegger - 2007 - Philosophy of Science 74 (5):839-847.
    The spontaneous emergence of signaling has already been studied in terms of standard evolutionary dynamics of signaling games. Standard evolutionary dynamics is given by the replicator equations. Thus, it is not clear whether the results for standard evolutionary dynamics depend crucially on the functional form of the replicator equations. In this paper I show that the basic results for the replicator dynamics of signaling games carry over to a number of other evolutionary dynamics. ‡This (...)
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  45.  32
    Human Kinship, From Conceptual Structure to Grammar.Doug Jones - 2010 - Behavioral and Brain Sciences 33 (5):367.
    Research in anthropology has shown that kin terminologies have a complex combinatorial structure and vary systematically across cultures. This article argues that universals and variation in kin terminology result from the interaction of (1) an innate conceptual structure of kinship, homologous with conceptual structure in other domains, and (2) principles of optimal, communication active in language in general. Kin terms from two languages, English and Seneca, show how terminologies that look very different on the surface may result from variation in (...)
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  46.  15
    Language Games and Natural Reactions.David Rubinstein - 2004 - Journal for the Theory of Social Behaviour 34 (1):55–71.
    Ludwig Wittgenstein imagines a variety of eccentric social practices—like a tribe trained “to give no expression of feeling of any kind”. But he also speaks of “the common behavior of mankind” that is rooted in “natural/primitive reactions”. This emphasis on the uniformities of human behavior raises questions about the plausibility of some of his imagined language games. Indeed, it suggests the claim of evolutionary psychologists that there are biologically based human universals that shape social practices. But in contrast (...)
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  47.  25
    On an Evolutionary Foundation of Neuroeconomics: Burkhard C. Schipper.Burkhard C. Schipper - 2008 - Economics and Philosophy 24 (3):495-513.
    Neuroeconomics focuses on brain imaging studies mapping neural responses to choice behaviour. Economic theory is concerned with choice behaviour but it is silent on neural activities. We present a game theoretic model in which players are endowed with an additional structure – a simple “nervous system” – and interact repeatedly in changing games. The nervous system constrains information processing functions and behavioural functions. By reinterpreting results from evolutionary game theory, we suggest that nervous systems can develop to “function (...)
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  48.  53
    Stable Games.Josef Hofbauer - unknown
    We introduce a new class of population games called stable games. These games are characterized by self-defeating externalities: when agents revise their strategies, the improvements in the payoffs of strategies to which revising players are switching are always exceeded by the improvements in the payoffs of strategies which revising players are abandoning. We show that stable games subsume many well-known classes of examples, including zero-sum games, games with an interior ESS, wars of attrition, and (...)
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  49.  31
    An Evolutionary Theory of Commons Management.Peter Richerson - manuscript
    Our aim in this chapter is to draw lessons from current theory on the evolution of human cooperation for the management of contemporary commons. Evolutionary theorists have long been interested in cooperation but social scientists have documented patterns of cooperation in humans that present unusual problems for conventional evolutionary theory (and for rational choice explanations as well). Humans often cooperate with nonrelatives and are prone to cooperate in one-shot games. Cooperation is quite dependent on social institutions. We (...)
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  50. An Evolutionary Theory of Commons Management.Rob Boyd - manuscript
    Our aim in this chapter is to draw lessons from current theory on the evolution of human cooperation for the management of contemporary commons. Evolutionary theorists have long been interested in cooperation but social scientists have documented patterns of cooperation in humans that present unusual problems for conventional evolutionary theory (and for rational choice explanations as well). Humans often cooperate with nonrelatives and are prone to cooperate in one-shot games. Cooperation is quite dependent on social institutions. We (...)
     
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