Journal of the ACM (JACM)
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Synthesizing constraint expressions
Communications of the ACM
Preliminary report on a system for general space planning
Communications of the ACM
The complexity of satisfiability problems
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Structural Descriptions and Inexact Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Consistent Labeling Problem: Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Examination of Probabilistic Value-Ordering Heuristics
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Collaborative Learning for Constraint Solving
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
The consistent labeling problem in temporal reasoning
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
The consistent labeling problem in temporal reasoning
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
The complexity of constraint satisfaction in prolog
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
CSCLP'04 Proceedings of the 2004 joint ERCIM/CoLOGNET international conference on Recent Advances in Constraints
| Hi-index | 0.00 |
A new parameter is introduced to characterize a type of search problem of broad relevance in artificial intelligence, operations research and symbolic logic. This parameter, which we call inter-variable compatibility, is particularly important in that complexity analyses incorporating it are able to capture the dependence of problem complexity on search order used by an algorithm. Thus compatibility-based theories can provide a theoretical basis for the extraction of heuristics for choosing good search orderings-a long-sought goal for such problems, since it can lead to significant savings during search. We carry out expected-complexity analyses for the traditional backtrack algorithm as well as for two more recent algorithms that have been found empirically to be significant improvements: forward checking and word-wise forward checking. We extract compatibility-based ordering-heuristics from the theory for forward checking. Preliminary experimental results are presented showing the large savings that result from their use. Similar savings can be expected for other algorithms when heuristics taking account of inter-variable compatibilities are used. Our compatibility-based theories also provide a more precise way of predicting which algorithm is best for a given problem.