An interactive method of inducing operator descriptions

McCluskey, T.L., Richardson, N.E. and Simpson, R.M. (2002) An interactive method of inducing operator descriptions. In: Proceedings of the sixth international conference on articial intelligence planning systems. AAAI Press, pp. 121-130. ISBN 9781577351429

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Abstract

Specifying operator descriptions for planning domain models, especially using standard pre- and post condition symbolism, is a slow and painstaking process. This is because one is trying to capture what is essentially procedural knowledge in a declarative way in a language whose design is influenced by the construction of planning engines. The problem is acute if nonplanning experts are undertaking this task, and/or the operators are complex or hierarchical. In this paper we describe opmaker, a method in which the domain expert specifies the declarative structure of the domain (in terms of an object hierarchy, object descriptions etc) and provides training operator sequences. This input is made in the context of a tools environment supporting planner domain acquisition and modelling. opmaker then induces a set of parameterised operator descriptions from these examples, removing the need for the user to become involved in complex parameter manipulation within the underlying symbolic, logicbased language. We discuss the empirical evaluation of the implemented induction algorithm with the help of a range of domains, and draw conclusions for future work.

Item Type:	Book Chapter
Additional Information:	Proceedings of the sixth international conference on articial intelligence planning systems (AIPS-2002), Toulouse, France, 2002 © Association for the Advancement of Artificial Intelligence
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools:	School of Computing and Engineering School of Computing and Engineering > Pedagogical Research Group School of Computing and Engineering > High-Performance Intelligent Computing 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
Depositing User:	Cherry Edmunds
Date Deposited:	30 Oct 2008 16:14
Last Modified:	29 Mar 2018 16:16
URI:	http://eprints.hud.ac.uk/id/eprint/2516

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