Evolutionary Constitution of Game Player Agents

抄録

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 (ES). In this method, we attempt to acquire better state evaluation function by evolving weights and structure simultaneously.