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- W4312751566 abstract "A combination of multi-step technology and policy iteration approach is introduced into the consistency control of multi-agent systems in this article. The multi-step technique is improved and applied to a multi-agent systems, and a multi-step policy iteration based on Q-learning is put forward. Through a finite number of multi-step iterations in advance, the multi-agent system can converge faster and achieve the desired goal. The proof of algorithm convergence is also given later. The optimal Q-function together with optimal control law are estimated respectively by constructing approximators through an ActorCritic neural network framework. Finally, a simulation result verifies the superiority of the this approach." @default.
- W4312751566 created "2023-01-05" @default.
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- W4312751566 date "2022-08-24" @default.
- W4312751566 modified "2023-10-16" @default.
- W4312751566 title "Optimal Consensus Control of Nonlinear Multi-Agent Systems Based on Multi-step Policy Iteration" @default.
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- W4312751566 doi "https://doi.org/10.1109/iai55780.2022.9976567" @default.
- W4312751566 hasPublicationYear "2022" @default.
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