腾讯会议号：234 318 283
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.
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， 国家级青年人才，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联合培养，哈佛大学进行学术访问，后入选美国西蒙斯博士后学者，获得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、博弈理论、群体决策和群体智能等。发表学术论文20余篇，包括多篇美国科学院院刊PNAS、Nature子刊、Science子刊论文。多项成果被国家基金委、中国教育网、宾夕法尼亚大学、北京大学官网报道。
