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ECAI 2006

Guiding Search Using Constraint-Level Advice

Conference Paper Constraints and Search Artificial Intelligence

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.

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Context

Venue
European Conference on Artificial Intelligence
Archive span
1982-2025
Indexed papers
5223
Paper id
80839776736330744