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Brian Skyrms [128]B. Skyrms [6]Bryan Skyrms [1]
  1. Brian Skyrms, Pragmatics, Logic, and Information Processing.
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  2. Brian Skyrms, Raffaele Argiento, Robin Pemantle & and Stanislav Volkov, Learning to Signal: Analysis of a Micro-Level Reinforcement Model.
    We consider the following signaling game. Nature plays first from the set {1, 2}. Player 1 (the Sender) sees this and plays from the set {A, B}. Player 2 (the Receiver) sees only Player 1’s play and plays from the set {1, 2}. Both players win if Player 2’s play equals Nature’s play and lose otherwise. Players are told whether they have won or lost, and the game is repeated. An urn scheme for learning coordination in this game is as (...)
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  3. Daniel C. Dennett, Brian Skyrms & Lawrence Sklar, -2001.
    Paul Valéry1 Valéry’s “Variation sur Descartes” excellently evokes the vanishing act that has haunted philosophy ever since Darwin overturned the Cartesian tradition. If my body is composed of nothing but a team of a few trillion robotic cells, mindlessly interacting to produce all the large-scale patterns that tradition would attribute to the nonmechanical workings of my mind, there seems to be nothing left over to be me. Lurking in Darwin’s shadow there is a bugbear: the incredible Disappearing Self.2 One of (...)
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  4. William Harms & Brian Skyrms, Evolution of Moral Norms.
    Moral norms are the rules of morality, those that people actually follow, and those that we feel people ought to follow, even when they don’t. Historically, the social sciences have been primarily concerned with describing the many forms that moral norms take in various cultures, with the emerging implication that moral norms are mere arbitrary products of culture. Philosophers, on the other hand, have been more concerned with trying to understand the nature and source of rules that all cultures ought (...)
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  5. Brian Skyrms, Fermat and Pascal on Probability.
    Italian writers of the fifteenth and sixteenth centuries, notably Pacioli (1494), Tartaglia (1556), and Cardan (1545), had discussed the problem of the division of a stake between two players whose game was interrupted before its close. The problem was proposed to Pascal and Fermat, probably in 1654, by the Chevalier de M´er´e, a gambler who is said to have had unusual ability “even for the mathematics.” The correspondence which ensued between Fermat and Pascal, was fundamental in the development of modern (...)
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  6. Brian Skyrms, A Dynamic Model of Social Network Formation.
    This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on April 27, 1999.
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  7. Brian Skyrms, Learning to Network.
    In species capable of learning, including our own, individuals can modify their behavior by some adaptive process. Important classes of behavior - mating, predation, coalitions, trade, signaling, and division of labor - involve interactions between individuals. The agents involved learn two things: with whom to interact and how to act. That is to say that adaptive dynamics operates both on structure and strategy.
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  8. Brian Skyrms, Network Formation by Reinforcement Learning: The Long and Medium Run.
    We investigate a simple stochastic model of social network formation by the process of reinforcement learning with discounting of the past. In the limit, for any value of the discounting parameter, small, stable cliques are formed. However, the time it takes to reach the limiting state in which cliques have formed is very sensitive to the discounting parameter. Depending on this value, the limiting result may or may not be a good predictor for realistic observation times.
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  9. Brian Skyrms, Evolution of Signaling Systems with Multiple Senders and Receivers.
    To coordinate action, information must be transmitted, processed, and utilized to make decisions. Transmission of information requires the existence of a signaling system in which the signals that are exchanged are coordinated with the appropriate content. Signaling systems in nature range from quorum signaling in bacteria [Schauder and Bassler (2001), Kaiser (2004)], through the dance of the bees [Dyer and Seeley (1991)], birdcalls [Hailman, Ficken, and Ficken (1985), Gyger, Marler and Pickert (1987), Evans, Evans, and Marler (1994), Charrier and (...)
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  10. Brian Skyrms, Time to Absorption in Discounted Reinforcement Models.
    Reinforcement schemes are a class of non-Markovian stochastic processes. Their non-Markovian nature allows them to model some kind of memory of the past. One subclass of such models are those in which the past is exponentially discounted or forgotten. Often, models in this subclass have the property of becoming trapped with probability 1 in some degenerate state. While previous work has concentrated on such limit results, we concentrate here on a contrary effect, namely that the time to become trapped may (...)
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  11. Brian Skyrms & Bill Harms, Evolution of Moral Norms.
    Moral norms are the rules of morality, those that people actually follow, and those that we feel people ought to follow, even when they don’t. Historically, the social sciences have been primarily concerned with describing the many forms that moral norms take in various cultures, with the emerging implication that moral norms are mere arbitrary products of culture. Philosophers, on the other hand, have been more concerned with trying to understand the nature and source of rules that all cultures ought (...)
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  12. Charles S. Chihara & Brian Skyrms (forthcoming). An International Journal for Epistemology, Methodology and Philosophy of Science. Synthese.
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  13. Simon M. Huttegger & Brian Skyrms (forthcoming). Learning to Transfer Information. Studia Logica.
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  14. B. Skyrms (forthcoming). Return of the Liar'. American Philosophical Quarterly.
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  15. Brian Skyrms (forthcoming). Grades of Inductive Skepticism. .
    There is not a unique inductive skeptical position; there are grades of inductive skepticism. There is nothing much to say about complete skepticism, but some more restricted skeptical positions may be profitably analyzed.
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  16. Brian Skyrms (2014). Social Dynamics. Oup Oxford.
    Brian Skyrms applies adaptive dynamics (of cultural evolution and individual learning) to social theory, investigating altruism, spite, fairness, trust, division of labor, and signaling. Correlation is seen to be fundamental. Spontaneous emergence of social structure and of signaling systems are examined in the context of learning dynamics.
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  17. Simon M. Huttegger & Brian Skyrms (2013). Strategic Interaction in Humans and Other Animals. Biological Theory 8 (2):125-126.
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  18. Simon M. Huttegger, Brian Skyrms & Kevin J. S. Zollman (2013). Probe and Adjust in Information Transfer Games. Erkenntnis:1-19.
    We study a low-rationality learning dynamics called probe and adjust. Our emphasis is on its properties in games of information transfer such as the Lewis signaling game or the Bala-Goyal network game. These games fall into the class of weakly better reply games, in which, starting from any action profile, there is a weakly better reply path to a strict Nash equilibrium. We prove that probe and adjust will be close to strict Nash equilibria in this class of games with (...)
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  19. Brian Skyrms (2013). Learning to Signal with Probe and Adjust – Corrigendum. Episteme 10 (3):333-333.
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  20. Brian Skyrms (2013). Natural Social Contracts. Biological Theory 8 (2):179-184.
    There are two fundamental problems for instituting a social contract. The first is cooperating to produce a surplus; the second is deciding how to divide this surplus. I represent each problem by a simple paradigm game, a Stag Hunt game for cooperating to produce a surplus, and a bargaining game for its division. I will discuss these simple games in isolation, and end by discussing their composition.
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  21. Brian Skyrms (2013). The Core Theory of Subjunctive Conditionals. Synthese 190 (5):923-928.
    Conditional probability and selection-function approaches to chancy subjunctive conditionals are compared in a simple and transparent setting. They are seen to be alternative ways of calculating the same quantity. This unification extends from core cases to more peripheral cases.
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  22. Brian Skyrms & Simon M. Huttegger (2013). Emergence of a Signaling Network with Probe and Adjust. In Kim Sterelny, Richard Joyce, Brett Calcott & Ben Fraser (eds.), Cooperation and its Evolution. MIT Press. 265.
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  23. B. Skyrms (2012). Ken Binmore * Rational Decisions. British Journal for the Philosophy of Science 63 (2):449-453.
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  24. Brian Skyrms (2012). From Zeno to Arbitrage: Essays on Quantity, Coherence, and Induction. Oxford University Press.
    Pt. I. Zeno and the metaphysics of quantity. Zeno's paradox of measure -- Tractarian nominalism -- Logical atoms and combinatorial possibility -- Strict coherence, sigma coherence, and the metaphysics of quantity -- pt. II. Coherent degrees of belief. Higher-order degrees of belief -- A mistake in dynamic coherence arguments? -- Dynamic coherence and probability kinematics -- Updating, supposing, and MAXENT -- The structure of radical probabilism -- Diachronic coherence and radical probabilism -- pt. III. Induction. Carnapian inductive logic for Markov (...)
     
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  25. Brian Skyrms (2012). Learning to Signal with Probe and Adjust. Episteme 9 (2):139-150.
    Research Articles Brian Skyrms, Episteme , FirstView Article.
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  26. Simon M. Huttegger, Brian Skyrms, Rory Smead & Kevin J. S. Zollman (2010). Evolutionary Dynamics of Lewis Signaling Games: Signaling Systems Vs. Partial Pooling. [REVIEW] 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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  27. B. Skyrms & K. J. S. Zollman (2010). Evolutionary Considerations in the Framing of Social Norms. 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 games. (...)
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  28. Brian Skyrms (2010). Signals: Evolution, Learning, and Information. OUP Oxford.
    Brian Skyrms presents a fascinating exploration of how fundamental signals are to our world. He uses a variety of tools -- theories of signaling games, information, evolution, and learning -- to investigate how meaning and communication develop. He shows how signaling games themselves evolve, and introduces a new model of learning with invention. The juxtaposition of atomic signals leads to complex signals, as the natural product of gradual process. Signals operate in networks of senders and receivers at all levels of (...)
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  29. Brian Skyrms (2010). The Flow of Information in Signaling Games. 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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  30. Brian Skyrms & Robin Pemantle (2010). Learning to Network. In Ellery Eells & James H. Fetzer (eds.), The Place of Probability in Science. Springer. 277--287.
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  31. Brian Skyrms (2009). Diachronic Coherence and Radical Probabilism. In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of Belief. Springer. 253--261.
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  32. Simon M. Huttegger & Brian Skyrms (2008). Emergence of Information Transfer by Inductive Learning. Studia Logica 89 (2):237 - 256.
    We study a simple game theoretic model of information transfer which we consider to be a baseline model for capturing strategic aspects of epistemological questions. In particular, we focus on the question whether simple learning rules lead to an efficient transfer of information. We find that reinforcement learning, which is based exclusively on payoff experiences, is inadequate to generate efficient networks of information transfer. Fictitious play, the game theoretic counterpart to Carnapian inductive logic and a more sophisticated kind of learning, (...)
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  33. B. Skyrms (2008). Review: Cristina Bicchieri: The Grammar of Society. [REVIEW] Mind 117 (465):167-170.
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  34. Brian Skyrms (2008). Presidential Address: Signals. Philosophy of Science 75 (5):489-500.
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  35. Brian Skyrms (2008). Signals. Philosophy of Science 75 (5).
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  36. Brian Skyrms (2008). Trust, Risk, and the Social Contract. Synthese 160 (1):21 - 25.
    The problem of trust is discussed in terms of David Hume’s meadow-draining example. This is analyzed in terms of rational choice, evolutionary game theory and a dynamic model of social network formation. The kind of explanation that postulates an innate predisposition to trust is seen to be unnecessary when social network dynamics is taken into account.
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  37. Brian Skyrms (2007). Dynamic Networks and the Stag Hunt: Some Robustness Considerations. Biological Theory 2 (1):7-9.
  38. Brian Skyrms (2006). Diachronic Coherence and Radical Probabilism. Philosophy of Science 73 (5):959-968.
    The question of diachronic coherence, coherence of degrees of belief across time, is investigated within the context of Richard Jeffrey’s radical probabilism. Diachronic coherence is taken as fundamental, and coherence results for degrees of belief at a single time, such as additivity, are recovered only with additional assumptions. Additivity of probabilities of probabilities is seen to be less problematic than additivity of first-order probabilities. Without any assumed model of belief change, diachronic coherence applied to higher-order degrees of belief yields the (...)
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  39. Brian Skyrms (2005). Dynamics of Conformist Bias. The Monist 88 (2):260-269.
    We compare replicator dynamics for some simple games with and without the addition of conformist bias. The addition of conformist bias can create equilibria, it can change the stability properties of existing equilibria, it may leave the equilibrium structure intact but change the relative size of basins of attraction, or it may do nothing at all. Examples of each of the foregoing are given.
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  40. Peter Vanderschraaf & Brian Skyrms (2003). Learning to Take Turns. Erkenntnis 59 (3):311 - 348.
    Learning to take turns in repeated game situations is a robust phenomenon in both laboratory experiments and in everyday life. Nevertheless, it has received little attention in recent studies of learning dynamics in games. We investigate the simplest and most obvious extension of fictitious play to a learning rule that can recognize patterns, and show how players using this rule can spontaneously learn to take turns.
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  41. Brian Skyrms (2002). Altruism, Inclusive Fitness, and "the Logic of Decision". Proceedings of the Philosophy of Science Association 2002 (3):S104-S111.
    We show how Richard Jeffrey’s The Logic of Decision provides the proper formalism for calculating expected fitness for correlated encounters in general. As an illustration, some puzzles about kin selection are resolved.
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  42. Brian Skyrms (2002). Critical Commentary on Unto Others. [REVIEW] Philosophy and Phenomenological Research 65 (3):697–701.
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  43. Brian Skyrms (2002). Review: Critical Commentary on Unto Others. [REVIEW] Philosophy and Phenomenological Research 65 (3):697 - 701.
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  44. Brian Skyrms (2002). Signals, Evolution and the Explanatory Power of Transient Information. Philosophy of Science 69 (3):407-428.
    Pre‐play signals that cost nothing are sometimes thought to be of no significance in interactions which are not games of pure common interest. We investigate the effect of pre‐play signals in an evolutionary setting for Assurance, or Stag Hunt, games and for a Bargaining game. The evolutionary game with signals is found to have dramatically different dynamics from the same game without signals. Signals change stability properties of equilibria in the base game, create new polymorphic equilibria, and change the basins (...)
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  45. S. L. Zabell, Brian Skyrms, Elliott Sober, Malcolm R. Forster, Wayne C. Myrvold, William L. Harper, Rob Clifton, Itamar Pitowsky, Robyn M. Dawes & David Faust (2002). 10. It All Adds Up: The Dynamic Coherence of Radical Probabilism It All Adds Up: The Dynamic Coherence of Radical Probabilism (Pp. S98-S103). [REVIEW] Philosophy of Science 69 (S3).
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  46. Brian Skyrms (2001). The Stag Hunt. Proceedings and Addresses of the American Philosophical Association 75 (2):31 - 41.
    If it was a matter of hunting a deer, everyone well realized that he must remain faithful to his post; but if a hare happened to pass within reach of one of them, we cannot doubt that he would have gone off in pursuit of it without scruple..." Rousseau's story of the hunt leaves many questions open. What are the values of a hare and of an individual's share of the deer given a successful hunt? What is the probability that (...)
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  47. Alan Hájek & Brian Skyrms (2000). Bayes or Bust? Philosophy and Phenomenological Research 60 (3):707-711.
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  48. Brian Skyrms (2000). Adaptive Dynamic Models and the Social Contract. Journal of Consciousness Studies 7 (1/2):335-339.
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  49. Brian Skyrms (2000). Game Theory, Rationality and Evolution of the Social Contract. Journal of Consciousness Studies 7 (1-2):1-2.
  50. Brian Skyrms (2000). Just Playing: Game Theory and the Social Contract Vol. 2, Ken Binmore. MIT Press, 1998, XXIII + 589 Pages. [REVIEW] Economics and Philosophy 16 (1):147-174.
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