Decentralized Learning for Optimality in Stochastic Dynamic Teams and Games with Local Control and Global State Information
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DOI: 10.1109/tac.2021.3121228
Abstract: Stochastic dynamic teams and games are rich models for decentralized systems and challenging testing grounds for multi-agent learning. Several algorithms exist for stochastic games, some with guarantees of convergence to equilibrium. However, there may be… read more here.
Keywords: teams games; optimality; global state; control ... See more keywords