Multi-Agent Distributed Deep Deterministic Policy Gradient for Partially Observable Tracking

Multi-Agent Distributed Deep Deterministic Policy Gradient for Partially Observable Tracking

In many existing multi-agent reinforcement learning tasks, each agent observes all the other agents from its own perspective. In addition, the training process is centralized, namely the critic of each agent can access the policies of all the agents. This scheme has certain limitations since every s...

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Bibliographic Details
Main Authors:	Dongyu Fan, Haikuo Shen, Lijing Dong
Format:	Article
Language:	English
Published:	MDPI AG 2021-10-01
Series:	Actuators
Subjects:	multi-agent systems deep reinforcement learning actor–critic partial observability
Online Access:	https://www.mdpi.com/2076-0825/10/10/268

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