Proceedings:
Vol. 19 (2009): Nineteenth International Conference on Automated Planning and Scheduling
Volume
Issue:
Vol. 19 (2009): Nineteenth International Conference on Automated Planning and Scheduling
Track:
Short Papers
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Abstract:
N-gram analysis provides a means of probabilistically predicting the next item in a sequence. Due originally to Shannon, it has proven an effective technique for word prediction in natural language processing and for gene sequence analysis. In this paper, we investigate the utility of n-gram analysis in predicting operator sequences in plans. Given a set of sample plans, we perform n-gram analysis to predict the likelihood of subsequent operators, relative to a partial plan. We identify several ways in which this information might be integrated into a planner. In this paper, we investigate one of these directions in further detail. Preliminary results demonstrate the promise of n-gram analysis as a tool for improving planning performance.
DOI:
10.1609/icaps.v19i1.13392
ICAPS
Vol. 19 (2009): Nineteenth International Conference on Automated Planning and Scheduling