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

Internet

https://www.mdpi.com/2073-8994/12/4/631

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