Cooperative Multi-Agent Reinforcement Learning With Approximate Model Learning

Cooperative Multi-Agent Reinforcement Learning With Approximate Model Learning

In multi-agent reinforcement learning, it is essential for agents to learn communication protocol to optimize collaboration policies and to solve unstable learning problems. Existing methods based on actor-critic networks solve the communication problem among agents. However, these methods have diff...

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Bibliographic Details
Main Authors: Young Joon Park, Young Jae Lee, Seoung Bum Kim
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Reinforcement learning
model-free method
multi-agent system
multi-agent cooperation
actor-critic method
deterministic policy gradient
Online Access:https://ieeexplore.ieee.org/document/9133381/

Internet

https://ieeexplore.ieee.org/document/9133381/

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