| Title | Evolutionary dynamics of zero-determinant strategies in repeated multiplayer games |
| Authors | Chen, Fang Wu, Te Wang, Long |
| Affiliation | Peking Univ, Coll Engn, Ctr Syst & Control, Beijing, Peoples R China Xidian Univ, Ctr Complex Syst, Xian, Peoples R China Peking Univ, Inst Artificial Intelligence, Ctr Multiagent Res, Beijing, Peoples R China |
| Keywords | COOPERATION EXTORTION |
| Issue Date | 21-Sep-2022 |
| Publisher | JOURNAL OF THEORETICAL BIOLOGY |
| Abstract | Several studies have confirmed the existence of zero-determinant (ZD) strategies in repeated social dilemmas since Press and Dyson's ingenious discovery of ZD strategies in iterated prisoner's dilemmas. However, less research studies evolutionary performance of multiplayer ZD strategies, especially from a theoretical perspective. Here, we use a state-clustering method to theoretically analyze evolutionary dynamics of two representative ZD strategies: generous ZD strategies and extortionate ZD strategies. We consider two new settings for multiplayer ZD strategies: competitions with all ZD strategies and competitions with all memory-one strategies, apart from the competitions between these strategies and some classical ones. Moreover, we investigate the influence of the level of generosity and extortion on evolutionary dynamics of generous and extortionate ZD strategies, which was commonly ignored in previous studies. Theoretical results show that players with limited generosity are at an advantageous place and extortioners extorting more severely hold their ground more readily. Our results may provide new insights into better understanding evolutionary dynamics of ZD strategies in repeated multiplayer games. (c) 2022 Elsevier Ltd. All rights reserved. |
| URI | http://hdl.handle.net/20.500.11897/649263 |
| ISSN | 0022-5193 |
| DOI | 10.1016/j.jtbi.2022.111209 |
| Indexed | SCI(E) |
| Appears in Collections: | 工学院 |
