A Confrontation Decision-Making Method with Deep Reinforcement Learning and Knowledge Transfer for Multi-Agent System

A Confrontation Decision-Making Method with Deep Reinforcement Learning and Knowledge Transfer for Multi-Agent System

In this paper, deep reinforcement learning (DRL) and knowledge transfer are used to achieve the effective control of the learning agent for the confrontation in the multi-agent systems. Firstly, a multi-agent Deep Deterministic Policy Gradient (DDPG) algorithm with parameter sharing is proposed to a...

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Bibliographic Details
Main Author:	Chunyang Hu
Format:	Article
Language:	English
Published:	MDPI AG 2020-04-01
Series:	Symmetry
Subjects:	deep deterministic policy gradient policy-based RL knowledge transfer momentum mechanism multi-agent systems
Online Access:	https://www.mdpi.com/2073-8994/12/4/631

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