Par-KAP: a knowledge acquisition tool for building practical planning systems

Authors:
Leliane Nunes De Barros;James Hendler;V. Richard Benjamins
Affiliations:
University of Maryland, Department of Computer Science, College Park, MD;University of Maryland, Department of Computer Science, College Park, MD;Articificial Intelligence Research Institute, CSIC, Bellaterra, Spain and University of Amsterdam, SWI, Amsterdam, The Netherlands
Venue:
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Year:
1997

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Abstract

Recently, attention has been focused on providing Knowledge Acquisition (KA) support for building practical planning systems. Such support is needed to guide a knowledge engineer in selecting planning methods, as well as for building and validating the planning knowledge-base for a given practical domain. Following current practice in knowledge acquisition, developing KA tools for planning requires that a number of planning knowledge components are made explicit. This includes explicating (i) a planning domain ontology, (ii) a library of problem-solving methods (PSMs) used in planning, and (iii) a set of domain requirements that are used to select a suitable PSM. In this paper, we summarize the planning knowledge components which we have identified in previous work, and, based on these, present an implementation (Par-KAP) that can exploit these models to aid knowledge engineers in constructing practical planning systems.