NOSCE HOSTEM: Searching with Opponent Models


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Title NOSCE HOSTEM: Searching with Opponent Models
Period 01 / 1997 - 12 / 2003
Status Completed
Dissertation Yes
Research number OND1261423


Artificial Intelligence (AI) is an interesting research area with challenging problems. One of the problems is the game of chess. Already at the start of AI research (around 1950) it was on the list of problems to be ``solved''. Here solving means building a program that could play at a par with or even stronger than the human world champion. In 1997 the chess system Deep Blue surprised the non-academic world by winning a match against the world champion Gary Kasparov. Some then believed that this victory was the end of chess as a research area, others argued that the game still was not solved and that many mysteries remained to be unravelled. For instance, the complex method of using opponent models in search was in the mid 1990s still in its infancy. The fact that Deep Blue team profited considerably from the co-operation with grandmasters who studied Kasparov's games and fed the system with knowledge on his style, can be considered as its actual incorporation in match play. The general goal of this research project is to investigate to which extent knowledge of the opponent can be used to improve computer game-playing.

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Supervisor Prof.dr. H.J. van den Herik
Co-supervisor J.W.H.M. Uiterwijk
Doctoral/PhD student Dr. H.H.L.M. Donkers


D16400 Information systems, databases

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