Abstract
Knowledge engineering in AI planning is the process that deals with the acquisition, validation and maintenance of planning domain models, and the selection and optimisation of appropriate planning machinery to work on them. Our aim is to research and develop rigorous methods for the acquisition, maintenance and validation of planning domain models. We aim to provide a tools environment suitable for use by domain experts in addition to experts in the field of AI planning. In this paper we describe such a method and illustrate it with screen-shots taken from an implemented Graphical Interface for Planning with Objects system called GIPO. The GIPO tools environment has been built to support an object centred approach to planning domain modelling. The principal innovation we present in this paper is a process of specifying domain operators that abstracts away much of the technical detail traditionally required in their specification. Such innovations we believe could ultimately open up the possibility of bringing planning technology to a wider public.
Keywords
- Domain Model
- Planning Domain
- Drive Operator
- Tool Environment
- Remote Agent
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2002 Springer-Verlag Berlin Heidelberg
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Simpson, R.M., McCluskey, T.L. (2002). A Tool Supported Structured Method for Planning Domain Acquisition. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_58
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DOI: https://doi.org/10.1007/3-540-48050-1_58
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