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  Adaptive dynamics of memory-one strategies in the repeated donation game

LaPorte, P., Hilbe, C., & Nowak, M. A. (2023). Adaptive dynamics of memory-one strategies in the repeated donation game. PLoS Computational Biology, 19(6): e1010987. doi:10.1371/journal.pcbi.1010987.

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 Creators:
LaPorte, Philip, Author
Hilbe, Christian1, Author                 
Nowak, Martin A., Author
Affiliations:
1Max Planck Research Group Dynamics of Social Behavior (Hilbe), Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_3164873              

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 Abstract: Human interactions can take the form of social dilemmas: collectively, people fare best if all cooperate but each individual is tempted to free ride. Social dilemmas can be resolved when individuals interact repeatedly. Repetition allows them to adopt reciprocal strategies which incentivize cooperation. The most basic model for direct reciprocity is the repeated donation game, a variant of the prisoner’s dilemma. Two players interact over many rounds; in each round they decide whether to cooperate or to defect. Strategies take into account the history of the play. Memory-one strategies depend only on the previous round. Even though they are among the most elementary strategies of direct reciprocity, their evolutionary dynamics has been difficult to study analytically. As a result, much previous work has relied on simulations. Here, we derive and analyze their adaptive dynamics. We show that the four-dimensional space of memory-one strategies has an invariant three-dimensional subspace, generated by the memory-one counting strategies. Counting strategies record how many players cooperated in the previous round, without considering who cooperated. We give a partial characterization of adaptive dynamics for memory-one strategies and a full characterization for memory-one counting strategies.

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Language(s): eng - English
 Dates: 2023-03-022023-06-132023-06-29
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1010987
 Degree: -

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Project name : E-DIRECT
Grant ID : 850529
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: PLoS Computational Biology
Source Genre: Journal
 Creator(s):
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 19 (6) Sequence Number: e1010987 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1