loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Wataru Fujita 1 ; Koichi Moriyama 2 ; Ken-ichi Fukui 1 and Masayuki Numao 1

Affiliations: 1 Osaka University, Japan ; 2 Nagoya Institute of Technology, Japan

Keyword(s): Multi-agent, Reinforcement Learning, Game Theory.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Software Engineering ; Symbolic Systems

Abstract: In our society, people engage in a variety of interactions. To analyze such interactions, we consider these interactions as a game and people as agents equipped with reinforcement learning algorithms. Reinforcement learning algorithms are widely studied with a goal of identifying strategies of gaining large payoffs in games; however, existing algorithms learn slowly because they require a large number of interactions. In this work, we constructed an algorithm that both learns quickly and maximizes payoffs in various repeated games. Our proposed algorithm combines two different algorithms that are used in the early and later stages of our algorithm. We conducted experiments in which our proposed agents played ten kinds of games in self-play and with other agents. Results showed that our proposed algorithm learned more quickly than existing algorithms and gained sufficiently large payoffs in nine games.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.191.165.192

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Fujita, W.; Moriyama, K.; Fukui, K. and Numao, M. (2016). Adaptive Two-stage Learning Algorithm for Repeated Games. In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-172-4; ISSN 2184-433X, SciTePress, pages 47-55. DOI: 10.5220/0005711000470055

@conference{icaart16,
author={Wataru Fujita. and Koichi Moriyama. and Ken{-}ichi Fukui. and Masayuki Numao.},
title={Adaptive Two-stage Learning Algorithm for Repeated Games},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2016},
pages={47-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005711000470055},
isbn={978-989-758-172-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Adaptive Two-stage Learning Algorithm for Repeated Games
SN - 978-989-758-172-4
IS - 2184-433X
AU - Fujita, W.
AU - Moriyama, K.
AU - Fukui, K.
AU - Numao, M.
PY - 2016
SP - 47
EP - 55
DO - 10.5220/0005711000470055
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic