Authors
Masato Nagayoshi1, *, Simon J. H. Elderton1, Hisashi Tamaki2
1Niigata College of Nursing, 240 shinnan-cho, Joetsu, Niigata 943-0147, Japan
2Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, Japan
*Corresponding author. Email: [email protected]
Corresponding Author
Masato Nagayoshi
Received 24 November 2020, Accepted 11 March 2021, Available Online 27 May 2021.
DOI
https://doi.org/10.2991/jrnal.k.210521.002How to use a DOI?
Keywords
Reinforcement learning; role differentiation; meta-parameter; waveform changing; state space filter
Abstract
Recently, there have been many studies on Multi-agent Reinforcement Learning (MARL) in which each autonomous agent obtains its own control rule by RL. Here, we hypothesize that different agents having individuality is more effective than uniform agents in terms of role differentiation in MARL. We have previously proposed a promoting method of role differentiation using a waveform changing parameter in MARL. In this paper, we confirm the effectiveness of role differentiation by introducing the waveform changing parameter into a state space filter through computational examples using “Pursuit Game” as a multi-agent task.
Copyright
© 2021 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).