Reinforcement learning on a futures market simulator

Koichi Moriyama, Mitsuhiro Matsumoto, Ken Ichi Fukui, Satoshi Kurihara, Masayuki Numao

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In recent years, it becomes vigorous to forecast a market by using machine learning methods. Since they assume that each trader's individual decisions do not affect market prices at all, most existing works use a past market data set. Meanwhile there is an attempt to analyze economic phenomena by constructing a virtual market simulator, where human and artificial traders really make trades. Since prices in the market are determined by every trader's decisions, it is more realistic and the assumption cannot be applied any more. In this work, we design and evaluate several reinforcement learners on a futures market simulator U-Mart (Unreal Market as an Artificial Research Testbed). After that, we compare our learner to the previous champions of U-Mart competitions.

本文言語English
ホスト出版物のタイトルAgent and Multi-Agent Systems
ホスト出版物のサブタイトルTechnologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings
出版社Springer Verlag
ページ42-52
ページ数11
ISBN(印刷版)9783540728290
DOI
出版ステータスPublished - 2007 1 1
外部発表はい
イベント1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007 - Wroclaw, Poland
継続期間: 2007 5 312007 6 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4496 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007
国/地域Poland
CityWroclaw
Period07/5/3107/6/1

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

フィンガープリント

「Reinforcement learning on a futures market simulator」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル