Evidence for Invariants in Local Search

Abstract

It is well known that the performance of a stochastic local search procedure depends upon the setting of its noise parameter, and that the optimal setting varies with the problem distribution. It is therefore desirable to develop general priniciples for tuning the procedures. We present two statistical measures of the local search process that allow one to quickly find the optimal noise settings. These properties are independent of the fine details of the local search strategies, and appear to be relatively independent of the structure of the problem domains. We applied these principles to the problem of evaluating new search heuristics, and discovered two promising new strategies.

Extracted Key Phrases

7 Figures and Tables

Statistics

02040'96'98'00'02'04'06'08'10'12'14'16
Citations per Year

441 Citations

Semantic Scholar estimates that this publication has 441 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{McAllester1997EvidenceFI, title={Evidence for Invariants in Local Search}, author={David A. McAllester and Bart Selman and Henry A. Kautz}, booktitle={AAAI/IAAI}, year={1997} }