{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T07:53:47Z","timestamp":1782460427343,"version":"3.54.5"},"reference-count":42,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Research Council Starting Grant","award":["850529"],"award-info":[{"award-number":["850529"]}]},{"name":"Max Planck Society"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Researchers have explored the performance of Iterated Prisoner\u2019s Dilemma strategies for decades, from the celebrated performance of Tit for Tat to the introduction of the zero-determinant strategies and the use of sophisticated learning structures such as neural networks. Many new strategies have been introduced and tested in a variety of tournaments and population dynamics. Typical results in the literature, however, rely on performance against a small number of somewhat arbitrarily selected strategies, casting doubt on the generalizability of conclusions. In this work, we analyze a large collection of 195 strategies in thousands of computer tournaments, present the top performing strategies across multiple tournament types, and distill their salient features. The results show that there is not yet a single strategy that performs well in diverse Iterated Prisoner\u2019s Dilemma scenarios, nevertheless there are several properties that heavily influence the best performing strategies. This refines the properties described by Axelrod in light of recent and more diverse opponent populations to: be nice, be provocable and generous, be a little envious, be clever, and adapt to the environment. More precisely, we find that strategies perform best when their probability of cooperation matches the total tournament population\u2019s aggregate cooperation probabilities. The features of high performing strategies help cast some light on why strategies such as Tit For Tat performed historically well in tournaments and why zero-determinant strategies typically do not fare well in tournament settings.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012644","type":"journal-article","created":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T18:21:32Z","timestamp":1735237292000},"page":"e1012644","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["Properties of winning Iterated Prisoner\u2019s Dilemma strategies"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2943-3622","authenticated-orcid":true,"given":"Nikoleta E.","family":"Glynatsi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Knight","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc","family":"Harper","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,12,26]]},"reference":[{"issue":"4489","key":"pcbi.1012644.ref001","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.1126\/science.7466396","article-title":"The evolution of cooperation","volume":"211","author":"R Axelrod","year":"1981","journal-title":"science"},{"issue":"1","key":"pcbi.1012644.ref002","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1177\/002200278002400101","article-title":"Effective Choice in the Prisoner\u2019s Dilemma","volume":"24","author":"R Axelrod","year":"1980","journal-title":"Journal of Conflict Resolution"},{"issue":"6357","key":"pcbi.1012644.ref003","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1038\/355250a0","article-title":"Tit for tat in heterogeneous populations","volume":"355","author":"MA Nowak","year":"1992","journal-title":"Nature"},{"issue":"6432","key":"pcbi.1012644.ref004","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/364056a0","article-title":"A strategy of win-stay, lose-shift that outperforms tit-for-tat in the Prisoner\u2019s Dilemma game","volume":"364","author":"M Nowak","year":"1993","journal-title":"Nature"},{"key":"pcbi.1012644.ref005","first-page":"202","volume-title":"Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living Systems","author":"B Beaufils","year":"1997"},{"issue":"26","key":"pcbi.1012644.ref006","doi-asserted-by":"crossref","first-page":"10409","DOI":"10.1073\/pnas.1206569109","article-title":"Iterated Prisoner\u2019s Dilemma contains strategies that dominate any evolutionary opponent","volume":"109","author":"WH Press","year":"2012","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1012644.ref007","unstructured":"Tzafestas E. 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