This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial...
Abstract. By developing an intelligent computer system that will provide commentary of chess moves in a comprehensible, user-friendly and instructive way, we are trying to use the ...
Matej Guid, Martin Mozina, Jana Krivec, Aleksander...
In this paper we present TDLEAF( ), a variation on the TD( ) algorithm that enables it to be used in conjunction with game-tree search. We present some experiments in which our che...
A general technique is proposed to deal with the formalization of intuition and human-oriented concepts in competition thinking games like chess, such as defensive play, attack, t...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...