报告题目：
Strategy evolution on dynamic and higher-order networks (动态和高阶网络上的策略演化)
时间：
2024年12月26日 9:30-11:00
地点：
经济管理学院B208
报告人简介：
苏奇，上海交通大学电子信息与电气工程学院副教授， 国家海外高层次青年人才，上海市海外高层次人才，上海市浦江人才。分别于华中科技大学、北京大学取得取得学士、博士学位。曾在美国波士顿大学开展博士学位联合培养，哈佛大学进行学术访问。曾获得美国西蒙斯基金会为期三年的独立经费资助，在宾夕法尼亚大学数学系和生物系从事学术研究。主要研究兴趣为网络科学、群体决策和博弈理论等。在PNAS、Nature Human Behaviour、 Nature Computational Science、Science Advances等期刊上发表研究论文20余篇。多项成果被国家基金委员会、中国教育网等报道。获得西蒙斯博士后学者奖，全国大数据与社会计算会议新星奖等。
报告摘要：
Collective intelligence, which emphasizes that systems can rely on cooperation and coordination among individuals to achieve goals that are impossible by any individual alone to achieve, proves to be an increasingly promising research direction in artificial intelligence. In collective intelligence, one of the most cutting-edge questions is how and when cooperation and coordination emerge, especially when individuals have the cognitive ability to make their own behavioral decisions and simultaneously face conflicts between their own and collective interests. Classic game theory based on the assumption of perfect rationality has predicted a convergence towards the Nash Equilibrium state, i.e., the collapse of cooperation. In this talk, I give a brief overview of studies about system structures’ effects on the evolution of cooperation. Besides, I present four works about the evolution of cooperation on complex networks, which respectively accounts for the directionality of interactions, the coupling of multiple systems, the time-varying features of system structures, and the higher-order effects. We derive rigorous analytical conditions to predict when a system evolves away from the Nash Equilibrium and reveal that the interaction directionality, the coupling of multiple systems, structural changes, and the high-order interactions, can promote the evolution of cooperation by orders of magnitude.
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