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ACG
2003
Springer
13 years 7 months ago
DF-PN in Go: An Application to the One-Eye Problem
Akihiro Kishimoto, Martin Müller 0003
ACG
2003
Springer
13 years 7 months ago
First Experimental Results of ProbCut Applied to Chess
ProbCut is a selective-search enhancement to the standard alpha
Albert Xin Jiang, Michael Buro
ACG
2003
Springer
13 years 8 months ago
The 7-piece Perfect Play Lookup Database for the Game of Checkers
Many research teams and individuals have computed endgame databases for the game of chess which use the distance-to-mate metric, enabling their software to forecast the number of m...
Ed Trice, Gil Dodgen
ACG
2003
Springer
13 years 8 months ago
Building the Checkers 10-piece Endgame Databases
Jonathan Schaeffer, Yngvi Björnsson, Neil Bur...
ACG
2003
Springer
13 years 8 months ago
Search versus Knowledge: An Empirical Study of Minimax on KRK
This article presents the results of an empirical experiment designed to gain insight into what is the effect of the minimax algorithm on the evaluation function. The experiment’...
Aleksander Sadikov, Ivan Bratko, Igor Kononenko
ACG
2003
Springer
13 years 8 months ago
Evaluation Function Tuning via Ordinal Correlation
Heuristic search effectiveness depends directly upon the quality of heuristic evaluations of states in the search space. We show why ordinal correlation is relevant to heuristic se...
Dave Gomboc, T. Anthony Marsland, Michael Buro
ACG
2003
Springer
13 years 8 months ago
New Games Related to Old and New Sequences
We define an infinite class of 2-pile subtraction games, where the amount that can be subtracted from both piles simultaneously, is a function f of the size of the piles. Wytho...
Aviezri S. Fraenkel
ACG
2003
Springer
13 years 8 months ago
Evaluation in Go by a Neural Network using Soft Segmentation
In this article a neural network architecture is presented that is able to build a soft segmentation of a two-dimensional input. This network architecture is applied to position ev...
Markus Enzenberger
ACG
2003
Springer
13 years 8 months ago
Opponent-Model Search in Bao: Conditions for a Successful Application
Abstract Opponent-Model search is a game-tree search method that explicitly uses knowledge of the opponent. There is some risk involved in using Opponent-Model search. Both the pre...
H. H. L. M. Donkers, H. Jaap van den Herik, Jos W....
ACG
2003
Springer
13 years 8 months ago
Monte-Carlo Go Developments
We describe two Go programs,  ¢¡¤£¦¥ and  ¢¡¤§¨£ , developed by a Monte-Carlo approach that is simpler than Bruegmann’s (1993) approach. Our method is based on Abra...
Bruno Bouzy, Bernard Helmstetter