Par-KAP: a Knowledge Acquisition Tool for Building Practical Planning Systems
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Planning and Scheduling. Pages 1246-1252.
Abstract
Recently, attention has b ee n focused on providing Knowledge Acquisition (KA) support for building practical planning systems. Such support is needed to guide a knowledge engin ee r in selecting planning methods, as well as for building and validating th e planning knowl edge-base for a given practical domain . Following current practice in knowledge acquisition, developing KA tools for planning requir es that a number of planning knowledge components are made explicit. This includ es explicating (i) a planning domain onto logy, (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 summariz e the planning knowledge components which we have identified in previous work , and, based on these , present an implementation (Par-KAP) that can exp loit th ese models to aid knowledge engineers in constructing practical planning systems.
@inproceedings{ijcai1997p180,
title = {Par-KAP: a Knowledge Acquisition Tool for Building Practical Planning Systems},
author = {de Barros, Leliane Nunes and Hendler, James A. and Benjamins, V. Richard},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {1246--1252},
year = {1997},
note = {Planning and Scheduling},
url = {https://ijcai.org/proceedings/1997/180},
}
TY - CPAPER TI - Par-KAP: a Knowledge Acquisition Tool for Building Practical Planning Systems AU - de Barros, Leliane Nunes AU - Hendler, James A. AU - Benjamins, V. Richard T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 1246 EP - 1252 UR - https://ijcai.org/proceedings/1997/180 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: