Nash Equilibria in Multi-Agent Motor Interactions |
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Authors: | Daniel A Braun Pedro A Ortega Daniel M Wolpert |
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Institution: | 1.Computational and Biological Learning Laboratory, Department of
Engineering, University of Cambridge, Cambridge, United Kingdom;2.Bernstein Center for Computational Neuroscience, Freiburg,
Germany;University College London, United Kingdom |
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Abstract: | Social interactions in classic cognitive games like the ultimatum game or the
prisoner''s dilemma typically lead to Nash equilibria when multiple
competitive decision makers with perfect knowledge select optimal strategies.
However, in evolutionary game theory it has been shown that Nash equilibria can
also arise as attractors in dynamical systems that can describe, for example,
the population dynamics of microorganisms. Similar to such evolutionary
dynamics, we find that Nash equilibria arise naturally in motor interactions in
which players vie for control and try to minimize effort. When confronted with
sensorimotor interaction tasks that correspond to the classical
prisoner''s dilemma and the rope-pulling game, two-player motor
interactions led predominantly to Nash solutions. In contrast, when a single
player took both roles, playing the sensorimotor game bimanually, cooperative
solutions were found. Our methodology opens up a new avenue for the study of
human motor interactions within a game theoretic framework, suggesting that the
coupling of motor systems can lead to game theoretic solutions. |
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