Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Denotational abstract interpretation of logic programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Games and full completeness for multiplicative linear logic
Journal of Symbolic Logic
A Game Semantics Foundation for Logic Programming (Extended Abstract)
PLILP '98/ALP '98 Proceedings of the 10th International Symposium on Principles of Declarative Programming
Games Semantics for Full Propositional Linear Logic
LICS '95 Proceedings of the 10th Annual IEEE Symposium on Logic in Computer Science
Believe it or not, AJM's games model is a model of classical linear logic
LICS '97 Proceedings of the 12th Annual IEEE Symposium on Logic in Computer Science
Towards Ludics Programming: Interactive Proof Search
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
How to correctly prune tropical trees
AISC'10/MKM'10/Calculemus'10 Proceedings of the 10th ASIC and 9th MKM international conference, and 17th Calculemus conference on Intelligent computer mathematics
Hi-index | 0.00 |
Alpha-Beta is a well known optimized algorithm used to compute the values of classical combinatorial games, like chess and checkers. The known proofs of correctness of Alpha-Beta do rely on very specific properties of the values used in the classical context (integers or reals), and on the finiteness of the game tree. In this paper we prove that Alpha-Beta correctly computes the value of a game tree even when these values are chosen in a much wider set of partially ordered domains, which can be pretty far apart from integer and reals, like in the case of the lattice of idempotent substitutions or ex-equations used in logic programming. We do so in a more general setting that allows us to deal with infinite games, and we actually prove that for potentially infinite games Alpha-Beta correctly computes the value of the game whenever it terminates. This correctness proofs allows us to apply Alpha-Beta to new domains, like constraint logic programming.