A Virtual Play Environment and Game Strategy Analysis System Using Imitation Learning Agents
Masayuki Ueno, Wada Shinjiro, Tomoyuki Takami · 2020
By using machine learning to learn the behavior of human players in a logical board game, It is possible to create an agent that mimics the strategy of a human player. These imitation learning agents can be used for various educational purposes. In this paper, we describe a virtual play environment and game strategy analysis system that can be constructed using imitation learning agents in a logical board game.