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A Runtime Performance Predictor for Selecting Tabu TenuresOne of the drawbacks of parameter based systems, such as tabu search, is the difficulty of finding the correct parameter for a particular problem. Often, rule-of-thumb advice is given which may have little or no applicability to the domain or problem instance at hand. This paper describes the application of a general technique, Runtime Performance Predictors (RPP) which can be used to determine, in an efficient manner, the correct tabu tenure for a particular problem instance. The details of the approach and a demonstration using a variant of GSAT are presented.
Document ID
20020039791
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Allen, John A.
(NASA Ames Research Center Moffett Field, CA United States)
Minton, Steven N.
(University of Southern California Los Angeles, CA United States)
Date Acquired
August 20, 2013
Publication Date
January 1, 1997
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: Fifteenth International Joint Conference on Artificial Intelligence
Location: Nagaya
Country: Japan
Start Date: August 23, 1997
End Date: August 29, 1997
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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