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FLAIRS
2007

Random Subsets Support Learning a Mixture of Heuristics

11 years 10 months ago
Random Subsets Support Learning a Mixture of Heuristics
Problem solvers, both human and machine, have at their disposal many heuristics that may support effective search. The efficacy of these heuristics, however, varies with the problem class, and their mutual interactions may not be well understood. The long-term goal of our work is to learn how to select appropriately from among a large body of heuristics, and how to combine them into a mixture that works well on a specific class of problems. The principal result reported here is that randomly chosen subsets of heuristics can improve the identification of an appropriate mixture of heuristics. A self-supervised learner uses this method here to learn to solve constraint satisfaction problems quickly and effectively.
Smiljana Petrovic, Susan L. Epstein
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where FLAIRS
Authors Smiljana Petrovic, Susan L. Epstein
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