Variational Inequality Methods for Multi-Agent Reinforcement Learning: Performance and Stability Gains

Multi-agent reinforcement learning (MARL) presents unique challenges as agents learn strategies through experiences. Gradient-based methods are often sensitive to hyperparameter selection and initial random seed variations. Concurrently, significant advances have been made in solving Variational Ine...

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Hauptverfasser:	Sidahmed, Baraah A. M, Chavdarova, Tatjana
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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