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Conceptual struture of a multiagent system Highlights: ❀ Assumed that the control constraint set is finite in order to argue about the computational efficiency of the agent-by-agent rollout algorithm. ❀ Proposed new autonomous multiagent rollout schemes for both finite and infinite horizon problems. The idea is to use a precomputed signaling policy, which embodies sufficient agent coordination to obviate the need for interagent communication during the on-line implementation of the algorithm. ❀ Finally mention that the idea of agent-by-agent rollout also applies within the context of challenging deterministic discrete/combinatorial optimization problems, which involve constraints that couple the controls of different stages. 推荐阅读: 美国工程院院士Dimitri P. Bertsekas: 强化学习及最优控制(71页PPT) 美国工程院院士Dimitri P. Bertsekas: 基于特征的聚合与深度强化学习 Dimitri Bertsekas, "Multiagent Reinforcement Learning:Rollout and Policy Iteration," IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 249-272, Feb. 2021.
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