Strategies anticipating a difference in search depth using opponent-model search

Theoretical Computer Science

Volumn 252, Issue 1-2, 2001, Pages 83-104

  Gao, Xinbo ^a   Iida, Hiroyuki ^b   Uiterwijk, Jos W H M ^c   Van den Herik, H Jaap ^c  

^a XIDIAN UNIVERSITY   (China)

^b SHIZUOKA UNIVERSITY   (Japan)

^c MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

2 pruning; Opponent modelling; Othello; Speculative play

Indexed keywords

COMPUTER SIMULATION; MATHEMATICAL MODELS; THEOREM PROVING;

SPECULATIVE PLAYS;

GAME THEORY;

EID: 0034915471     PISSN: 03043975     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3975(00)00077-3     Document Type: Article

References (19)

1. Some methods of controlling the tree search in chess programs
2. A generalized quiescence search algorithm
3. ProbCut: An effective selective extension of the alpha-beta algorithm
4. Pruning algorithms for multi-model adversary search
5. Potential applications of opponent-model search; Part 1: The domain of applicablity
6. Tutoring strategies in game-tree search
7. Gains and risks of OM search
8. Cooperative strategies for pair playing
9. Are there practical alternatives to alpha-beta?
10. Robocup: The robot world cup initiative
11. An analysis of alpha-beta pruning
12. Relative efficiency of alpha-beta implementations
13. An empirical comparison of pruning strategies in game trees
14. The efficiency of the alpha-beta search on trees with branch-dependent terminal node scores
15. Best-first fixed-depth minimax algorithms
16. Game tree searching by min/max approximation