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Signaling in sensorimotor interactions

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Leibfried,  F
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Grau-Moya,  J
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83827

Braun,  DA
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Sensorimotor Learning and Decision-Making, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Leibfried, F., Grau-Moya, J., & Braun, D. (2013). Signaling in sensorimotor interactions. Poster presented at Bernstein Conference 2013, Tübingen, Germany.


Cite as: https://hdl.handle.net/21.11116/0000-0001-4E55-9
Abstract
Communication relies on signals that convey information. In non-cooperative game theory, signaling games [1] are used to investigate under what conditions two players may communicate with each other when their ultimate aim is to maximize their own benefit. In this case, one player (the sender) possesses private information (the type) that the other player (the receiver) would like to know. However, signaling this information is costly. At the same time the receiver has control over a variable that influences the sender's payoff. The key question is under which circumstances so-called Perfect Bayesian Nash equilibria with reliable signaling occur. Here, we investigate whether human sensorimotor behavior conforms with optimal strategies corresponding to these equilibria [2]. We designed a sensorimotor task, where two participants controlled a two-dimensional cursor. Importantly, each player could control only one of the two dimensions. The sender's dimension could be used to communicate a target position that the receiver had to hit without knowing its location. The sender's aim was to maximize a point score displayed on a two-dimensional color map. The point score decreased with the magnitude of the signal and increased with the reach distance of the receiver. The sender therefore had a trade-off between communicating the real target distance with the hope that the receiver would learn to interpret this signal and give appropriate reward, and trying to avoid signaling costs. We found that participants developed strategies that resulted in separating equilibria as predicted by analytically derived game theoretic solutions.