Coevolution of neural Go players in a cultural environment

Abstract- We present experiments (co)evolving Go players based on artificial neural networks (ANNs) for a 5x5 board. ANN structure and weights are encoded in multi–chromosomal genotypes. In evolutionary scenarios a population of generalized multi–layer perceptrons (GMLPs) has to compete with a single Go program from a set of three players of different quality. Two coevolutionary approaches, namely, a dynamically growing culture, and a fixed–size elite represent the changing environment of the coevolving population. The playing quality of the (co)evolved players is measured by a strength value derived from games against the set of three programs. We also report on first experiments employing recurrent networks, which allow a direct structural representation of the Go board. Finally, the quality of all the best (co)evolved players is evaluated in a round robin tournament.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Helmut A. Mayer, Peter Maier
• Keywords: Artificial Intelligence, Artificial Neural Networks, CEC 2005, Go Players, Single Go Program