Evolutionary constitution of game player agents

In this paper, we propose a constitution method of game player agent that adopts a neural network as a state evaluation function for the game player, and evolves its weights and structure by evolutionary strategy. In this method, we attempt to acquire a better state evaluation function by evolving weights and structure simultaneously.