Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
A parsing: fast exact Viterbi parse selection
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Diagnosis of discrete-event systems using satisfiability algorithms
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Domain-independent construction of pattern database heuristics for cost-optimal planning
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Additive pattern database heuristics
Journal of Artificial Intelligence Research
Directed model checking with distance-preserving abstractions
SPIN'06 Proceedings of the 13th international conference on Model Checking Software
SAS+ planning as satisfiability
Journal of Artificial Intelligence Research
A SAT-based approach to cost-sensitive temporally expressive planning
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Many AI problems can be recast as finding an optimal path in a discrete state space. An abstraction defines an admissible heuristic function as the distances in a smaller state space where arbitrary sets of states are "aggregated" into single states. A special case are pattern database (PDB) heuristics, which aggregate states if they agree on the state variables inside the pattern. Explicit-state abstraction is more flexible, explicitly aggregating selected pairs of states in a process that interleaves composition of abstractions with abstraction of the composites. The increased flexibility gains expressive power: sometimes, the real cost function can be represented concisely as an explicit-state abstraction, but not as a PDB. Explicit-state abstraction has been applied to planning and model checking, with highly promiSing empirical results.