{"oa":1,"department":[{"_id":"KrCh"}],"publication_identifier":{"issn":["2752-6542"]},"year":"2022","ddc":["000"],"ec_funded":1,"scopus_import":"1","quality_controlled":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"4","author":[{"first_name":"Alex","last_name":"McAvoy","full_name":"McAvoy, Alex"},{"full_name":"Kates-Harbeck, Julian","first_name":"Julian","last_name":"Kates-Harbeck"},{"first_name":"Krishnendu","last_name":"Chatterjee","full_name":"Chatterjee, Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X"},{"id":"2FDF8F3C-F248-11E8-B48F-1D18A9856A87","full_name":"Hilbe, Christian","orcid":"0000-0001-5116-955X","first_name":"Christian","last_name":"Hilbe"}],"article_type":"original","doi":"10.1093/pnasnexus/pgac141","tmp":{"image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"related_material":{"link":[{"relation":"software","url":"https://github.com/alexmcavoy/fmtl/"}]},"article_processing_charge":"Yes","intvolume":"         1","day":"01","project":[{"call_identifier":"H2020","name":"Formal Methods for Stochastic Models: Algorithms and Applications","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"}],"volume":1,"acknowledgement":"The authors are grateful to Jörg Oechssler for many helpful comments. A.M. was supported by a Simons Postdoctoral Fellowship (Math+X) at the University of Pennsylvania; K.C. was supported by the European Research Council Consolidator Grant 863818 (ForM-SMArt); and C.H. was supported by the European Research Council Starting Grant 850529 (E-DIRECT).","file_date_updated":"2024-08-06T07:33:30Z","article_number":"pgac141","has_accepted_license":"1","date_published":"2022-09-01T00:00:00Z","month":"09","date_updated":"2024-08-06T07:35:17Z","abstract":[{"text":"Across many domains of interaction, both natural and artificial, individuals use past experience to shape future behaviors. The results of such learning processes depend on what individuals wish to maximize. A natural objective is one’s own success. However, when two such “selfish” learners interact with each other, the outcome can be detrimental to both, especially when there are conflicts of interest. Here, we explore how a learner can align incentives with a selfish opponent. Moreover, we consider the dynamics that arise when learning rules themselves are subject to evolutionary pressure. By combining extensive simulations and analytical techniques, we demonstrate that selfish learning is unstable in most classical two-player repeated games. If evolution operates on the level of long-run payoffs, selection instead favors learning rules that incorporate social (other-regarding) preferences. To further corroborate these results, we analyze data from a repeated prisoner’s dilemma experiment. We find that selfish learning is insufficient to explain human behavior when there is a trade-off between payoff maximization and fairness.","lang":"eng"}],"citation":{"ieee":"A. McAvoy, J. Kates-Harbeck, K. Chatterjee, and C. Hilbe, “Evolutionary instability of selfish learning in repeated games,” <i>PNAS Nexus</i>, vol. 1, no. 4. Oxford University Press, 2022.","short":"A. McAvoy, J. Kates-Harbeck, K. Chatterjee, C. Hilbe, PNAS Nexus 1 (2022).","ista":"McAvoy A, Kates-Harbeck J, Chatterjee K, Hilbe C. 2022. Evolutionary instability of selfish learning in repeated games. PNAS Nexus. 1(4), pgac141.","ama":"McAvoy A, Kates-Harbeck J, Chatterjee K, Hilbe C. Evolutionary instability of selfish learning in repeated games. <i>PNAS Nexus</i>. 2022;1(4). doi:<a href=\"https://doi.org/10.1093/pnasnexus/pgac141\">10.1093/pnasnexus/pgac141</a>","mla":"McAvoy, Alex, et al. “Evolutionary Instability of Selfish Learning in Repeated Games.” <i>PNAS Nexus</i>, vol. 1, no. 4, pgac141, Oxford University Press, 2022, doi:<a href=\"https://doi.org/10.1093/pnasnexus/pgac141\">10.1093/pnasnexus/pgac141</a>.","apa":"McAvoy, A., Kates-Harbeck, J., Chatterjee, K., &#38; Hilbe, C. (2022). Evolutionary instability of selfish learning in repeated games. <i>PNAS Nexus</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/pnasnexus/pgac141\">https://doi.org/10.1093/pnasnexus/pgac141</a>","chicago":"McAvoy, Alex, Julian Kates-Harbeck, Krishnendu Chatterjee, and Christian Hilbe. “Evolutionary Instability of Selfish Learning in Repeated Games.” <i>PNAS Nexus</i>. Oxford University Press, 2022. <a href=\"https://doi.org/10.1093/pnasnexus/pgac141\">https://doi.org/10.1093/pnasnexus/pgac141</a>."},"publisher":"Oxford University Press","status":"public","publication":"PNAS Nexus","_id":"17061","language":[{"iso":"eng"}],"oa_version":"Published Version","publication_status":"published","type":"journal_article","title":"Evolutionary instability of selfish learning in repeated games","external_id":{"arxiv":["2105.06199"]},"file":[{"file_id":"17400","date_updated":"2024-08-06T07:33:30Z","file_name":"2022_PNASNexus_McAvoy.pdf","success":1,"content_type":"application/pdf","date_created":"2024-08-06T07:33:30Z","relation":"main_file","checksum":"79a8e3e4be7e8a2b407b4efddd65f3f3","creator":"dernst","access_level":"open_access","file_size":2410962}],"date_created":"2024-05-28T14:23:12Z"}