EXPERIMENTS WITH A LEARNING COMPONENT IN A GO-MOK U PLAYING PROGRAM

AI Classics/files/AI/classics/Machine Intelligence 1&2/MI1&2-Ch.6-Elcock&Murray.pdf 

INTRODUCTION This paper is a report on some preliminary work undertaken as part of a longer term study of the problems which arise in designing and implementing digital computer programs which'learn'. A program has been written which learns to play the board game'Go-Moku' using a particular learning mechanism to be described later. The program is to be regarded as an experimental tool by means of which the particular learning mechanism can be investigated in some depth. Go-Moku is a simple but not a trivial game with an intellectual content comparable with a game of draughts (checkers). Opinions have sometimes been expressed that there is nothing to be learnt (no pun intended!) by programming simple games. Present knowledge of programming learning is such that it is useful to experiment with programs operating in a simple task environment. It is not so much what game the program learns as how it learns it. It is emphasised that the object of the present work is not to write a program which plays a difficult game better than anyone or anything has played it before, but to isolate and investigate particular aspects of a learning process which might be valid over a range of ill-structured problems. For the record, however, the current learning programs learn to play a good (basically defensive) game. The modifications currently being made to the program should give it a learning capacity to become unbeatable.

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