Approximate Policy Iteration for Robust Stochastic Control of Multiagent Markov Decision Processes
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DOI: 10.1109/tac.2024.3510596
Abstract: In stochastic dynamic environments, multiagent Markov decision processes have emerged as a versatile paradigm for studying sequential decision-making problems of fully cooperative multiagent systems. However, the optimality of the derived policies is usually sensitive to… read more here.
Keywords: control; markov decision; decision; multiagent markov ... See more keywords