DocumentCode
1692970
Title
New Approximate Strategies for Playing Sum Games Based on Subgame Types
Author
Zaky, Manal M. ; Andraos, Cherif R S ; Ghoneim, Salma A.
Author_Institution
Dept. of Comput. & Syst. Eng., Ain Shams Univ., Cairo
fYear
2006
Firstpage
418
Lastpage
422
Abstract
In this work, we investigate the potential of combining artificial intelligence (AI) tree-search algorithms with the algorithms of combinatorial game theory to provide more efficient strategies for playing sum games based on subgame types. Two new approximate strategies are developed and tested using a specified game model. Both strategies achieve higher performance than approximate strategies previously proposed in literature without being computationally more expensive
Keywords
artificial intelligence; game theory; tree searching; approximate strategy; artificial intelligence; combinatorial game theory; subgame type; sum games; tree-search algorithm; Artificial intelligence; Costs; Game theory; High performance computing; Humans; Minimax techniques; Runtime; Systems engineering and theory; Temperature; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Systems, The 2006 International Conference on
Conference_Location
Cairo
Print_ISBN
1-4244-0271-9
Electronic_ISBN
1-4244-0272-7
Type
conf
DOI
10.1109/ICCES.2006.320484
Filename
4115544
Link To Document