A Novel and Efficient Influence-Seeking Exploration in Deep Multiagent Reinforcement Learning

A Novel and Efficient Influence-Seeking Exploration in Deep Multiagent Reinforcement Learning

Although recent years witnessed notable success for a cooperative setting in multi-agent reinforcement learning (MARL), efficient explorations are still challenging primarily due to the complex dynamics of inter-agent interactions constituting the high dimension of action spaces. For an efficient ex...

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Bibliographic Details
Main Authors: Byunghyun Yoo, Devarani Devi Ningombam, Sungwon Yi, Hyun Woo Kim, Euisok Chung, Ran Han, Hwa Jeon Song
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Multi-agent systems
reinforcement learning
deep learning
Online Access:https://ieeexplore.ieee.org/document/9764683/

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