Abstract
Fuzzified game tree search algorithm is based on the idea that the exact game tree evaluation is not required to find the best move. Therefore, pruning techniques may be applied earlier resulting in faster search and greater performance. Applied to an abstract domain, it outperforms the existing ones such as Alpha-Beta, PVS, Negascout, NegaC*, SSS*/ Dual* and MTD(f). In this paper we present experimental results in real domain games, where the proposed algorithm demonstrated 10 percent performance increase over the existing algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Marsland, T.A., Campbell, M.: Parallel Search of Strongly Ordered Game Trees. ACM Comput. Surv. (1982)
Pearl, J.: The solution for the branching factor of the alpha-beta pruning algorithm and its optimality. Communications of the ACM (1982)
Reinefeld, A.: An Improvement to the Scout Tree-Search Algorithm. ICCA Journal 6(4), 4–14 (1983)
Reinefeld, A.: Spielbaum-Suchverfahren. Informatik-Fachbericht, vol. 200. Springer, Heidelberg (1989)
Weill, J.C.: The NegaC* search. ICCA Journal (March 1992)
Plaat, A., Schaeffer, J., Pijls, W., de Bruin, A.: A New Paradigm for Minimax Search, Technical Report EUR-CS-95-03 (1994)
Plaat, A., Schaeffer, J., Pijls, W., de Bruin, A.: Best-First and Depth-First Minimax Search in Practice. In: Proceedings of Computing Science in The Netherlands (1995)
Plaat, A., Schaeffer, J., Pijls, W., de Bruin, A.: An Algorithm Faster than NegaScout and SSS* in Practice. In: Computer Strategy Game Programming Workshop at the World Computer Chess Championship (1995)
Plaat, A., Schaeffer, J., Pijls, W., de Bruin, A.: Best-First Fixed-Depth Minimax Algorithms. Artificial Intelligence 87 (1996)
Björnsson, Y.: Selective Depth-First Game-Tree Search. Ph.D. thesis, University of Alberta (2002)
Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn. Pearson Education, Inc., Upper Saddle River (2010)
Rutko, D.: Fuzzified Algorithm for Game Tree Search. In: Second Brazilian Workshop of the Game Theory Society, BWGT 2010 (2010)
Rutko, D.: Fuzzified Algorithm for Game Tree Search with Statistical and Analytical Evaluation, Scientific Papers, vol. 770, pp. 90–111. University of Latvia (2011)
Hey That’s My Fish - German Board Games, http://www.mrbass.org/boardgames/heythatsmyfish/
Review of Hey! That’s My Fish! – RPGnet, http://www.rpg.net/reviews/archive/11/11936.phtml
Hey! That’s My Fish! Remarkable Depth for Minimal Rules, http://playthisthing.com/hey-thats-my-fish
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rutko, D. (2011). Fuzzified Tree Search in Real Domain Games. In: Batyrshin, I., Sidorov, G. (eds) Advances in Artificial Intelligence. MICAI 2011. Lecture Notes in Computer Science(), vol 7094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25324-9_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-25324-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25323-2
Online ISBN: 978-3-642-25324-9
eBook Packages: Computer ScienceComputer Science (R0)