A heuristic search algorithm with modifiable estimate
Artificial Intelligence
Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Artificial Intelligence
Sorting with fixed-length reversals
Discrete Applied Mathematics - Special volume on computational molecular biology
Artificial intelligence: a new synthesis
Artificial intelligence: a new synthesis
Complexity analysis admissible heuristic search
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Search Algorithms Under Different Kinds of Heuristics—A Comparative Study
Journal of the ACM (JACM)
Time complexity of iterative-deepening-A
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Disjoint pattern database heuristics
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
On the asymptotic performance of IDA*
Annals of Mathematics and Artificial Intelligence
Memory-Bounded A* Graph Search
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
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
Memory-efficient A* heuristics for multiple sequence alignment
Eighteenth national conference on Artificial intelligence
Journal of the ACM (JACM)
Maximizing over multiple pattern databases speeds up heuristic search
Artificial Intelligence
Duality in permutation state spaces and the dual search algorithm
Artificial Intelligence
Compressing Pattern Databases with Learning
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Space-efficient memory-based heuristics
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Dual search in permutation state spaces
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Predicting the performance of IDA* with conditional distributions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Additive pattern database heuristics
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
A general theory of additive state space abstractions
Journal of Artificial Intelligence Research
Domain-dependent single-agent search enhancements
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
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
Breadth-first heuristic search
Artificial Intelligence
Memory-based heuristics for explicit state spaces
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A* search with inconsistent heuristics
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Relative-Order Abstractions for the Pancake Problem
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Predicting the performance of IDA* using conditional distributions
Journal of Artificial Intelligence Research
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
Hierarchical A *: searching abstraction hierarchies efficiently
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Towards rational deployment of multiple heuristics in A*
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In the field of heuristic search it is usually assumed that admissible heuristics are consistent, implying that consistency is a desirable attribute. The term ''inconsistent heuristic'' has, at times, been portrayed negatively, as something to be avoided. Part of this is historical: early research discovered that inconsistency can lead to poor performance for A^@? (nodes might be re-expanded many times). However, the issue has never been fully investigated, and was not re-considered after the invention of IDA^@?. This paper shows that many of the preconceived notions about inconsistent heuristics are outdated. The worst-case exponential time of inconsistent heuristics is shown to only occur on contrived graphs with edge weights that are exponential in the size of the graph. Furthermore, the paper shows that rather than being something to be avoided, inconsistent heuristics often add a diversity of heuristic values into a search which can lead to a reduction in the number of node expansions. Inconsistent heuristics are easy to create, contrary to the common perception in the AI literature. To demonstrate this, a number of methods for achieving effective inconsistent heuristics are presented. Pathmax is a way of propagating inconsistent heuristic values in the search from parent to children. This technique is generalized into bidirectional pathmax (BPMX) which propagates values from a parent to a child node, and vice versa. BPMX can be integrated into IDA^@? and A^@?. When inconsistent heuristics are used with BPMX, experimental results show a large reduction in the search effort required by IDA^@?. Positive results are also presented for A^@? searches.