Honte, a Go-Playing Program Using Neural Nets
نویسنده
چکیده
The go-playing program Honte is described. It uses neural nets together with more conventional AI-methods like alpha-beta search. A neural net is trained by supervised learning to imitate local shapes made in a database of expert games. A second net is trained to estimate the safety of groups by self play using TD(λ)learning. A third net is trained to estimate territorial potential of unoccupied points, also based on self play and TD(λ)-learning. Although the program has not yet reached the level of the best commercial go-programs, results are encouraging.
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