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Please use this identifier to cite or link to this item: http://hdl.handle.net/2014/39046

Title: Robust local search for spacecraft operations using adaptive noise
Authors: Fukunaga, Alex S.
Rabideau, Gregg
Chien, Steve
Keywords: planning
scheduling
autonomy
machine learning
Issue Date: 23-Jun-2004
Publisher: Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2004.
Citation: International Workshop on Planning and Schedule for Space, Darmstadt, Germany, June 23-25, 2004
Abstract: Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.
URI: http://hdl.handle.net/2014/39046
Appears in Collections:JPL TRS 1992+

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