Why AC-3 is Almost Always Better than AC4 for Establishing Arc Consistency in CSPs
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Constraint Satisfaction Problems. Pages 239-246.
Abstract
On the basis of its optimal asymptotic time complexity, AC-4 is often considered the best algorithm for establishing arc consistency in constraint satisfaction problems (CSPs). In the present work, AC3 was found to be much more efficient th~m AC-4, for CSPs with a variety of features. (Variable pairs were in lexical order, ~md in AC-3 they were added to the end of the list of pairs.) This is supported by arguments for the superiority of AC-3 over most of the nmge of constraint satisfiabilities ~md for the unlikelihood of conditions leading to worst-case perfonmmce. The efficiency of AC-4 is affected by the order of variable testing in Phase 1 ('setting up' phase); perform~mce in this phase can thus be enhanced, and this establishes initial conditions for Phase 2 that improve its performance. But, since AC-3 is improved by the smne orderings, it still outperforms AC-4 in most cases.
@inproceedings{ijcai1993p34,
title = {Why AC-3 is Almost Always Better than AC4 for Establishing Arc Consistency in CSPs},
author = {Wallace, Richard J.},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {239--246},
year = {1993},
note = {Constraint Satisfaction Problems},
url = {https://ijcai.org/proceedings/1993/34},
}
TY - CPAPER TI - Why AC-3 is Almost Always Better than AC4 for Establishing Arc Consistency in CSPs AU - Wallace, Richard J. T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 239 EP - 246 UR - https://ijcai.org/proceedings/1993/34 ER -Copied
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