Multi-Agent, Human-Agent and Beyond: A Survey on Cooperation in Social
  Dilemmas
Hao Guo Chunjiang Mu Yang Chen Chen Shen Shuyue Hu Zhen Wang
The study of cooperation within social dilemmas has long been a fundamental
topic across various disciplines, including computer science and social
science. Recent advancements in Artificial Intelligence (AI) have significantly
reshaped this field, offering fresh insights into understanding and enhancing
cooperation. This survey examines three key areas at the intersection of AI and
cooperation in social dilemmas. First, focusing on multi-agent cooperation, we
review the intrinsic and external motivations that support cooperation among
rational agents, and the methods employed to develop effective strategies
against diverse opponents. Second, looking into human-agent cooperation, we
discuss the current AI algorithms for cooperating with humans and the human
biases towards AI agents. Third, we review the emergent field of leveraging AI
agents to enhance cooperation among humans. We conclude by discussing future
research avenues, such as using large language models, establishing unified
theoretical frameworks, revisiting existing theories of human cooperation, and
exploring multiple real-world applications.