How computers play chess
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Feature construction for game playing
Machines that learn to play games
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Automatic heuristic construction in a complete general game player
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Propositional Automata and Cell Automata: Representational Frameworks for Discrete Dynamic Systems
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
General game playing in AI research and education
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Generic heuristic approach to general game playing
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
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The General Game Playing (GGP) problem is concerned with developing systems capable of playing many different games, even games the system has never encountered before. Successful GGP agents must be able to extract relevant features from the formal game description and construct effective search heuristics. In this article, we present a procedure by which autonomous General Game Playing agents can generate effective and efficient search heuristics from the formal game description. The major aspect of our approach is an innovative technique to automatically extract critical features from the game structure. Our method has been incorporated into a fully implemented system that came in fourth place at the second General Game Playing Competition held at AAAI-06.