The integration of a priori knowledge into a Go playing neural network, www.cgl.ucsf.edu/go/Programs/ neurogo-html/NeuroGo.html

The best current computer Go programs are hand crafted expert sys-tems. They are using conventional AI technics such as pattern matching, rule based systems and goal oriented selective search. Due to the increas-ing complexity of managing this kind of knowledge representation by hand, the playing strength of these programs is still far from human master level. This article describes methods for integrating expert Go knowledge into a learning articial neural network. These methods are implemented in the programNeuroGo. The network learns by playing against itself using tem-poral dierence learning and backpropagation. The expert knowledge that is implemented at present in NeuroGo is simple compared with a conven-tional computer Go program. Despite of this, NeuroGo is able to achieve a playing strength which is equal to a conventional program playing at a medium level.