Learning to improve both efficiency and quality of planning

Authors:
Tara A. Estlin;Raymond J. Mooney
Affiliations:
Department of Computer Sciences, University of Texas at Austin, Austin, TX;Department of Computer Sciences, University of Texas at Austin, Austin, TX
Venue:
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Year:
1997

Citing 16
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Abstract

In order to rank the performance of machine learning algorithms, many researchers conduct experiments on benchmark data sets. Since most learning algorithms have domain-specific parameters, it is a popular custom to adapt these parameters to obtain a ...