Automatically generating abstractions for planning
Artificial Intelligence
Quantitatively relating abstractness to the accuracy of admissible heuristics
Artificial Intelligence
Synthesis of an efficient tactical theorem prover for the game of go
ACM Computing Surveys (CSUR) - Special issue: electronic supplement to the September 1998 issue
Experiments with Automatically Created Memory-Based Heuristics
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Recent Progress in the Design and Analysis of Admissible Heuristic Functions
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
CG '00 Revised Papers from the Second International Conference on Computers and Games
Lambda-Search in Game Trees - with Application to Go
CG '00 Revised Papers from the Second International Conference on Computers and Games
Theoretical Computer Science
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Some games have abstract properties that can be used to design admissible heuristics on moves. These admissible heuristics are useful to speed up search. They work well with depth-bounded search algorithms such as Gradual Abstract Proof Search that select moves based on the distance to the goal. We analyze the benefits of these admissible heuristics on moves for rules generation and search. We give experimental results that support our claim for the game of AtariGo.