Reinforcement Learning on a Futures Market Simulator
Дата
Авторы
Moriyama,Koichi
Matsumoto,Mitsuhiro
Fukui,Ken-ichi
Kurihara,Satoshi
Numao,Masayuki
Journal Title
Journal ISSN
Volume Title
Издатель
Journal of Universal Computer Science
Аннотация
Описание
In recent years, market forecasting by machine learning methods has been flourishing.Most existing works use a past market data set, because they assume that each trader's individual decisions do not affect market prices at all. Meanwhile, there have been attempts to analyzeeconomic phenomena by constructing virtual market simulators, in which human and artificial traders really make trades. Since prices in a market are, in fact, determined by every trader'sdecisions, a virtual market is more realistic, and the above assumption does not apply. In this work, we design several reinforcement learners on the futures market simulator U-Mart (UnrealMarket as an Artificial Research Testbed) and compare our learners with the previous champions of U-Mart competitions empirically.
Ключевые слова
reinforcement learning , market simulation