Group Formation by Group Joining and Opinion Updates Via Multi-Agent Online Gradient Ascent [AI-eXplained]

This article aims to exemplify best-response dynamics and multi-agent online learning by group formation. This extended abstract provides a summary of the full paper in IEEE Computational Intelligence Magazine on the special issue AI-eXplained (AI-X). The full paper includes interactive components t...

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Bibliographic Details
Published in:IEEE computational intelligence magazine 2023-11, Vol.18 (4), p.60-61
Main Authors: Lin, Chuang-Chieh, Hung, Chih-Chieh, Lu, Chi-Jen, Chen, Po-An
Format: Magazinearticle
Language:English
Subjects:
Artificial intelligence
Gradient methods
Heuristic algorithms
Multi-agent systems
Multiagent systems
Nash equilibrium
Regularization
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Summary:This article aims to exemplify best-response dynamics and multi-agent online learning by group formation. This extended abstract provides a summary of the full paper in IEEE Computational Intelligence Magazine on the special issue AI-eXplained (AI-X). The full paper includes interactive components to facilitate interested readers to grasp the idea of pure-strategy Nash equilibria and how the system of strategic agents converges to a stable state by the decentralized online gradient ascent with and without regularization.
ISSN:1556-603X
1556-6048
1556-6048
1556-603X
DOI:10.1109/MCI.2023.3304084