We introduce a method of learning spatial probability distributions for discrete gridded domains. We develop a decision tree based approach, which we call Spatial Probability Trees (SPTs).
We apply SPTs to computer Go to predict expert moves. The learned SPTs can then be used to provide advice to Monte Carlo based computer Go players. We specifically demonstrate that SPTs and SPT forests can be used to significantly improve the playing strength of a state-of-the-art computer Go player that uses Upper Confidence Bounds for Trees.
Zachery Tidwell (2012) Expert Move Prediction for Computer Go using Spatial Probability Trees. Master's Thesis, School of Computer Science, University of Oklahoma.
The code for the thesis can be released on request.
Created by amcgovern [at] ou.edu.
Last modified June 12, 2017 12:57 PM