A Multi-agent Reinforcement Learning Method for Role Differentiation Using State Space Filters with Fluctuation Parameters

Masato Nagayoshi; Simon J. H. Elderton; Hisashi Tamaki

doi:10.2991/jrnal.k.210521.002

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Volume 8, Issue 1, June 2021, Pages 6 - 9

A Multi-agent Reinforcement Learning Method for Role Differentiation Using State Space Filters with Fluctuation Parameters

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: nagayosi@niigata-cn.ac.jp

Corresponding Author

Masato Nagayoshi

Received 24 November 2020, Accepted 11 March 2021, Available Online 27 May 2021.

DOI: 10.2991/jrnal.k.210521.002 How 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 Atlantis Press B.V.
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/).

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Journal: Journal of Robotics, Networking and Artificial Life
Volume-Issue: 8 - 1
Pages: 6 - 9
Publication Date: 2021/05/27
ISSN (Online): 2352-6386
ISSN (Print): 2405-9021
DOI: 10.2991/jrnal.k.210521.002 How to use a DOI?
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/).

Cite this article

ris enw bib

TY  - JOUR
AU  - Masato Nagayoshi
AU  - Simon J. H. Elderton
AU  - Hisashi Tamaki
PY  - 2021
DA  - 2021/05/27
TI  - A Multi-agent Reinforcement Learning Method for Role Differentiation Using State Space Filters with Fluctuation Parameters
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 6
EP  - 9
VL  - 8
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.210521.002
DO  - 10.2991/jrnal.k.210521.002
ID  - Nagayoshi2021
ER  -

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