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  Emergence and suppression of cooperation by action visibility in transparent games

Unakafov, A. M., Schultze, T., Gail, A., Moeller, S., Kagan, I., Eule, S., et al. (2020). Emergence and suppression of cooperation by action visibility in transparent games. PLoS Computational Biology, 16(1): (in press). doi:10.1371/journal.pcbi.1007588.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-7BD7-F Version Permalink: http://hdl.handle.net/21.11116/0000-0005-7BD8-E
Genre: Journal Article

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Unakafov, Anton M.1, Author              
Schultze, T., Author
Gail, A., Author
Moeller, S., Author
Kagan, I., Author
Eule, Stephan2, Author              
Wolf, Fred2, Author              
Affiliations:
1Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063289              
2Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063286              

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 Abstract: Real-world agents, humans as well as animals, observe each other during interactions and choose their own actions taking the partners' ongoing behaviour into account. Yet, classical game theory assumes that players act either strictly sequentially or strictly simultaneously without knowing each other's current choices. To account for action visibility and provide a more realistic model of interactions under time constraints, we introduce a new game-theoretic setting called transparent games, where each player has a certain probability of observing the partner's choice before deciding on its own action. By means of evolutionary simulations, we demonstrate that even a small probability of seeing the partner's choice before one's own decision substantially changes the evolutionary successful strategies. Action visibility enhances cooperation in an iterated coordination game, but reduces cooperation in a more competitive iterated Prisoner's Dilemma. In both games, "Win-stay, lose-shift" and "Tit-for-tat" strategies are predominant for moderate transparency, while a "Leader-Follower" strategy emerges for high transparency. Our results have implications for studies of human and animal social behaviour, especially for the analysis of dyadic and group interactions.

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Language(s): eng - English
 Dates: 2020-01-09
 Publication Status: Published online
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 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1007588
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Title: PLoS Computational Biology
Source Genre: Journal
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Pages: - Volume / Issue: 16 (1) Sequence Number: (in press) Start / End Page: - Identifier: -