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ICTAI
2010
IEEE

Combining Learning Techniques for Classical Planning: Macro-operators and Entanglements

8 years 1 months ago
Combining Learning Techniques for Classical Planning: Macro-operators and Entanglements
Planning techniques recorded a significant progress during recent years. However, many planning problems remain still hard even for modern planners. One of the most promising approaches is gathering additional knowledge by using learning techniques. Well known sort of knowledge - macro-operators, formalized like `normal` planning operators, represent a sequence of primitive planning operators. The other sort of knowledge consists of pruning unnecessary operators' instances (actions) by investigating connections (entanglements) between operators and initial or goal predicates. Advantageously, macro-operators and entanglements can be encoded directly in planning domains (or problems) and common planning systems can be applied on them. In this paper, we will show how we can put these approaches together. We will provide an experimental evaluation showing that combining these learning techniques can improve the planning process.
Lukás Chrpa
Added 04 Mar 2011
Updated 04 Mar 2011
Type Journal
Year 2010
Where ICTAI
Authors Lukás Chrpa
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