A New Machine-Learning Technique Applied to the Game of Checkers

Abstract

This paper described a recent refinement of the machine--learning process employed by Samuel (1) in connection with his development of a checker playing program. Samuels checker player operates in much the same way a human player does; by looking ahead, and by making a qualitative judgment of the strength of the board positions it encounters. A machine learning process is applied to the development of an accurate procedure for making this strength evaluation of board positions. Before discussing my modifications to Samuels learning process, I should like to describe briefly Samuel's strength evaluation procedure, and the associated learning process.