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Artificial Intelligence - Lecture notes in computer science 178
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
An iterative algorithm for the Reeve's puzzle
The Computer Journal - Special issue on safety and security parallel computation
Criticizing solutions to relaxed models yields powerful admissible heuristics
Information Sciences: an International Journal
An improved fixed-parameter algorithm for vertex cover
Information Processing Letters
Time complexity of iterative-deepening-A
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Vertex cover: further observations and further improvements
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Disjoint pattern database heuristics
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Divide and Conquer Bidirectional Search: First Results
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Divide-and-Conquer Frontier Search Applied to Optimal Sequence Alignment
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AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Best-first frontier search with delayed duplicate detection
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Upper bounds for vertex cover further improved
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Finding optimal solutions to the twenty-four puzzle
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Finding optimal solutions to Rubik's cube using pattern databases
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Journal of the ACM (JACM)
Finding optimal solutions to the graph partitioning problem with heuristic search
Annals of Mathematics and Artificial Intelligence
Maximizing over multiple pattern databases speeds up heuristic search
Artificial Intelligence
Duality in permutation state spaces and the dual search algorithm
Artificial Intelligence
Scaling Search with Pattern Databases
Model Checking and Artificial Intelligence
Compressing Pattern Databases with Learning
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Multi-valued Pattern Databases
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
GP-rush: using genetic programming to evolve solvers for the rush hour puzzle
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Domain-independent construction of pattern database heuristics for cost-optimal planning
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Analyzing the performance of pattern database heuristics
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Learning from multiple heuristics
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Explicit-state abstraction: a new method for generating heuristic functions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
A general theory of additive state space abstractions
Journal of Artificial Intelligence Research
Recent progress in heuristic search: a case study of the four-peg towers of Hanoi problem
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Dual lookups in pattern databases
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Fixed-parameter tractability results for feedback set problems in tournaments
Journal of Discrete Algorithms
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
Combining perimeter search and pattern database abstractions
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
Using infeasibility to improve abstraction-based heuristics
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
Optimal admissible composition of abstraction heuristics
Artificial Intelligence
Predicting the performance of IDA* using conditional distributions
Journal of Artificial Intelligence Research
Implicit abstraction heuristics
Journal of Artificial Intelligence Research
Inconsistent heuristics in theory and practice
Artificial Intelligence
Solving the 24 puzzle with instance dependent pattern databases
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Experiments with multiple abstraction heuristics in symbolic verification
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Landmark-enhanced abstraction heuristics
Artificial Intelligence
The time complexity of A* with approximate heuristics on multiple-solution search spaces
Journal of Artificial Intelligence Research
Getting the most out of pattern databases for classical planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Learning optimal bayesian networks: a shortest path perspective
Journal of Artificial Intelligence Research
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We explore a method for computing admissible heuristic evaluation functions for search problems. It utilizes pattern databases (Culberson & Schaeffer, 1998), which are precomputed tables of the exact cost of solving various subproblems of an existing problem. Unlike standard pattern database heuristics, however, we partition our problems into disjoint sub-problems, so that the costs of solving the different subproblems can be added together without overestimating the cost of solving the original problem. Previously (Korf & Felner, 2002) we showed how to statically partition the sliding-tile puzzles into disjoint groups of tiles to compute an admissible heuristic, using the same partition for each state and problem instance. Here we extend the method and show that it applies to other domains as well. We also present another method for additive heuristics which we call dynamically partitioned pattern databases. Here we partition the problem into disjoint subproblems for each state of the search dynamically. We discuss the pros and cons of each of these methods and apply both methods to three different problem domains: the sliding-tile puzzles, the 4-peg Towers of Hanoi problem, and finding an optimal vertex cover of a graph. We find that in some problem domains, static partitioning is most effective. while in others dynamic partitioning is a better choice. In each of these problem domains, either statically partitioned or dynamically partitioned pattern database heuristics are the best known heuristics for the problem.