TY - JOUR
T1 - Multi-agent, human–agent and beyond
T2 - A survey on cooperation in social dilemmas
AU - Mu, Chunjiang
AU - Guo, Hao
AU - Chen, Yang
AU - Shen, Chen
AU - Hu, Die
AU - Hu, Shuyue
AU - Wang, Zhen
N1 - Publisher Copyright:
© 2024
PY - 2024/12/28
Y1 - 2024/12/28
N2 - 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.
AB - 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.
KW - Human–agent cooperation
KW - Multi-agent reinforcement learning
KW - Sequential social dilemma
KW - Social dilemma
UR - http://www.scopus.com/inward/record.url?scp=85204177130&partnerID=8YFLogxK
U2 - 10.1016/j.neucom.2024.128514
DO - 10.1016/j.neucom.2024.128514
M3 - 文章
AN - SCOPUS:85204177130
SN - 0925-2312
VL - 610
JO - Neurocomputing
JF - Neurocomputing
M1 - 128514
ER -