ECAI 2006
Guiding Search Using Constraint-Level Advice
Abstract
Constraint satisfaction problems are traditionally solved using some form of backtrack search that propagates constraints after each decision is made. The efficiency of search relies heavily on the use of good variable and value ordering heuristics. In this paper we show that constraints can also be used to guide the search process by actively proposing the next choice point to be branched on. We show that search effort can be reduced significantly.
Authors
Keywords
No keywords are indexed for this paper.
Context
- Venue
- European Conference on Artificial Intelligence
- Archive span
- 1982-2025
- Indexed papers
- 5223
- Paper id
- 80839776736330744