Improving a planner’s performance through online heuristic configuration of domain models

Vallati, Mauro, Chrpa, Lukáš and McCluskey, T.L. (2017) Improving a planner’s performance through online heuristic configuration of domain models. In: Proceedings of the 10th International Symposium on Combinatorial Search (SoCS). AAAI Press, pp. 171-172. ISBN 978-1577357902

PDF - Published Version Restricted to Repository staff only Download (125kB)

Abstract

The separation of planner logic from domain knowledge supports the use of reformulation and configuration techniques, such as macro-actions and entanglements, which transform the model representation in order to improve a planner’s performance. One drawback of such an approach is that it may require a potentially expensive training phase.
In this paper, we introduce heuristic approaches for the online configuration of planning domain models. The proposed
heuristics consider different aspects of PDDL-encoded operators for reordering such operators in the domain model, relying on the assumption that the way in which operators are encoded carries useful information about their expected use

Item Type:	Book Chapter
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Computer software
Schools:	School of Computing and Engineering School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
Related URLs:	Author Author Publisher Conference
Depositing User:	Mauro Vallati
Date Deposited:	17 May 2017 10:55
Last Modified:	28 Aug 2021 16:01
URI:	http://eprints.hud.ac.uk/id/eprint/31905

Downloads

Repository Staff Only: item control page

View Item