Beyond Optimal Play in Two-Person-Zerosum Games

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3221, Issue , 2004, Pages 749-759

  Lorenz, Ulf ^a  

^a UNIVERSITY OF PADERBORN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; TREES (MATHEMATICS);

DATABASE APPROACHES; GAME TREE SEARCH; GAME TREES; HUMAN PLAYERS; PRECOMPUTE; THEORETICAL ERRORS; ZERO-SUM GAME;

COMPUTER GAMES;

EID: 33747193691     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30140-0_66     Document Type: Article

References (18)

1. A. de Bruin A. Plaat, J. Schaeffer and W. Pijls. A minimax Algorithm better than SSS*. Artificial Intelligence, 87:255-293, 1999.
2. I. Althöfer. Root evaluation errors: How they arise and propagate. ICCA Journal, 11(3):55-63, 1988.
3. I. Althöfer. Generalized minmax algorithms are no better error correctors than minmax itself. In D.F. Beal, editor, Advances in Computer Chess 5, pages 265-282. North-Holland, 1990.
4. T.S. Anantharaman. Extension heuristics. ICCA Journal, 14(2):47-63, 1991.
5. B. Doerr and U. Lorenz. Error propagation in game trees, submitted to CG'04, 2004.
6. C. Donninger. Null move and deep search. ICCA Journal, 16(3):137-143, 1993.
7. P. J. Jansen. Kqkr: Speculativ thwarting a human opponent. ICCA Journal, 16(1):3-17, 1993.
8. th IJCAI, pages 322-327, Detroit, MI, 1989.
9. D.E. Knuth and R.W. Moore. An analysis of alpha-beta pruning. Artificial Intelligence, 6(4):293-326, 1975.
10. U. Lorenz. Controlled Conspiracy-2 Search. Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science (STACS), (H. Reichel, S.Tison eds), Springer LNCS, pages 466-478, 2000.
11. U. Lorenz and B. Monien. The secret of selective game tree search, when using random-error evaluations. Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science (STAGS) (H. Alt, A. Ferreira eds), Springer LNCS, pages 203-214, 2002.
12. D.A. McAllester. Conspiracy Numbers for Min-Max searching. Artificial Intelligence, 35(1):287-310, 1988.
13. J. Pearl. Heuristics - Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley Publishing Co., Reading, MA, 1984.
14. A. L. Reibman and B. W. Ballard. Non-Minimax Search Strategies for Use Against Fallible Opponents. Proceedings of the National Conference on Artificial Intelligence, AAAI, pages 338-342, 1983.
15. A. Reinefeld. Spielbaum - Suchverfahren. Springer, 1989.
16. J. Schaeffer. Conspiracy numbers. Artificial Intelligence, 43(1):67-84, 1990.
17. G. Schrüfer. Minimax-Suchen Kosten, Qualität und Algorithmen. Doctoral-Thesis, University of Braunschweig, Germany, 1988.
18. C.E. Shannon. Programming a computer for playing chess. Philosophical Magazine, 41:256-275, 1950.