Fashion plays such a crucial rule in the evolution of culture and society that it is regarded as a second nature to the human being. Also, its impact on economy is quite nontrivial. On what is fashionable, interestingly, there are two viewpoints that are both extremely widespread but almost opposite: conformists think that what is popular is fashionable, while rebels believe that being different is the essence. Fashion color is fashionable in the first sense, and Lady Gaga in the second. We investigate a model where the population consists of the afore-mentioned two groups of people that are located on social networks (a spatial cellular automata network and small-world networks). This model captures two fundamental kinds of social interactions (coordination and anti-coordination) simultaneously, and also has its own interest to game theory: it is a hybrid model of pure competition and pure cooperation. This is true because when a conformist meets a rebel, they play the zero sum matching pennies game, which is pure competition. When two conformists (rebels) meet, they play the (anti-) coordination game, which is pure cooperation. Simulation shows that simple social interactions greatly promote cooperation: in most cases people can reach an extraordinarily high level of cooperation, through a selfish, myopic, naive, and local interacting dynamic (the best response dynamic). We find that degree of synchronization also plays a critical role, but mostly on the negative side. Four indices, namely cooperation degree, average satisfaction degree, equilibrium ratio and complete ratio, are defined and applied to measure people's cooperation levels from various angles. Phase transition, as well as emergence of many interesting geographic patterns in the cellular automata network, is also observed.
Multi-Agent, Human-Agent and Beyond: A Survey on Cooperation in Social Dilemmas
Northwestern Polytechnical University（西北工业大学）；Tsinghua University（清华大学）；University of Auckland（奥克兰大学）；Kyushu University（九州大学）；The Hong Kong Polytechnic University（香港理工大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
Modeling Decision-Making with Will for Cooperation in Social Dilemmas
School of Intelligence Science and Technology, Peking University（北京大学智能学院）；State Key Laboratory of General Artificial Intelligence, BIGAI（通用人工智能国家重点实验室，BIGAI）；Law School, Peking University（北京大学法学院）
Evolutionary mechanisms that promote cooperation may not promote social welfare
Teesside University（提赛德大学）；University of Birmingham（伯明翰大学）；University of Maribor（马里博尔大学）；Community Healthcare Center Dr. Adolf Drolc Maribor（阿道夫·德罗尔奇博士马里博尔社区医疗中心）；Complexity Science Hub Vienna（维也纳复杂科学中心）；Kyung Hee University（庆熙大学）
Social welfare optimisation in well-mixed and structured populations
Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology (HCMUT), Vietnam（计算机科学与工程学院，胡志明市技术大学（HCMUT））；Vietnam National University - Ho Chi Minh City (VNU-HCM), Vietnam（越南国家大学-胡志明市（VNU-HCM））
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
Carnegie Mellon University；Foundations of Cooperative AI Lab (FOCAL)；Jinesis Lab, University of Toronto \& Vector Institute；ETH Z\" u rich；Max Planck Institute for Intelligent Systems, T\" u bingen, Germany
Shall We Team Up: Exploring Spontaneous Cooperation of Competing LLM Agents
Osaka University（大阪大学）；Kyoto University（京都大学）；University of Michigan（密歇根大学）；NII（信息学研究所）；Fordham University（福特汉姆大学）；University of California, Los Angeles（加利福尼亚大学洛杉矶分校）；University at Buffalo（布法罗大学）；Nagoya University（名古屋大学）
