Evolving Multi-Layer Neural Networks for Othello
Vassilis Makris, Dimitris Kalles · 2016
Othello has long been a favorite AI subject due to its very simple rules, its very low branching factor, its well defined strategic concepts and its dramatic changes in board topology as a game unfolds. In this paper, we investigate several neural network architectures using co-evolutionary learning techniques, with the objective to learn to play Othello strongly. Our resulting neural networks were able to learn to play the game at an expert-master level and to discover advanced strategies, within a few thousand generations, without any prior knowledge, beyond the game rules.