Cooperative and Competitive Multi-Agent Systems: From Optimization to Games

Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization. In a multi-agent system, agents with a certain degree of autonomy generate complex interactions due to th...

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Veröffentlicht in:IEEE/CAA journal of automatica sinica Jg. 9; H. 5; S. 763 - 783
Hauptverfasser: Wang, Jianrui, Hong, Yitian, Wang, Jiali, Xu, Jiapeng, Tang, Yang, Han, Qing-Long, Kurths, Jurgen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway Chinese Association of Automation (CAA) 01.05.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Physics,Humboldt University of Berlin,12489 Berlin,Germany
Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China%Department of Electrical and Computer Engineering,University of Windsor,Windsor,ON N9B 3P4,Canada%School of Science,Computing and Engineering Technologies,Swinburne University of Technology,Melbourne,VIC 3122,Australia%Potsdam Institute for Climate Impact Research,14473 Potsdam
Schlagworte:
Collaboration
Complex systems
Cooperative games
Correlation
Costs
counterfactual regret minimization
Decision making
distributed optimization
federated optimization
fictitious self-play
Focusing
Game theory
Games
mean field games
multi-agent reinforcement learning
Multiagent systems
non-cooperative games
Optimization
Privacy
multi-agent reinforcement learning
non-cooperative games
distributed optimization
federated optimization
mean field games
Cooperative games
counterfactual regret min-imization
fictitious self-play
ISSN:2329-9266, 2329-9274
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Zusammenfassung:Multi-agent systems can solve scientific issues related to complex systems that are difficult or impossible for a single agent to solve through mutual collaboration and cooperation optimization. In a multi-agent system, agents with a certain degree of autonomy generate complex interactions due to the correlation and coordination, which is manifested as cooperative/competitive behavior. This survey focuses on multi-agent cooperative optimization and cooperative/non-cooperative games. Starting from cooperative optimization, the studies on distributed optimization and federated optimization are summarized. The survey mainly focuses on distributed online optimization and its application in privacy protection, and overviews federated optimization from the perspective of privacy protection mechanisms. Then, cooperative games and non-cooperative games are introduced to expand the cooperative optimization problems from two aspects of minimizing global costs and minimizing individual costs, respectively. Multi-agent cooperative and non-cooperative behaviors are modeled by games from both static and dynamic aspects, according to whether each player can make decisions based on the information of other players. Finally, future directions for cooperative optimization, cooperative/non-cooperative games, and their applications are discussed.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2022.105506