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...
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...
The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation e...
Nicol N. Schraudolph, Peter Dayan, Terrence J. Sej...
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...