A Quality Framework for Automated Planning Knowledge Models

Mauro Vallati, Thomas Mccluskey

Abstract

Automated planning is a prominent Artificial Intelligence challenge, as well as a requirement for intelligent autonomous agents. A crucial aspect of automated planning is the knowledge model, that includes the relevant aspects of the application domain and of a problem instance to be solved. Despite the fact that the quality of the model has a strong influence on the resulting planning application, the notion of quality for automated planning knowledge models is not well understood, and the engineering process in building such models is still mainly an ad-hoc process. In order to develop systematic processes that support a more comprehensive notion of quality, this paper, building on existing frameworks proposed for general conceptual models, introduces a quality framework specifically focused on automated planning knowledge models.

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Paper Citation


in Harvard Style

Vallati M. and Mccluskey T. (2021). A Quality Framework for Automated Planning Knowledge Models.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 635-644. DOI: 10.5220/0010216806350644


in Bibtex Style

@conference{icaart21,
author={Mauro Vallati and Thomas Mccluskey},
title={A Quality Framework for Automated Planning Knowledge Models},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={635-644},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010216806350644},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A Quality Framework for Automated Planning Knowledge Models
SN - 978-989-758-484-8
AU - Vallati M.
AU - Mccluskey T.
PY - 2021
SP - 635
EP - 644
DO - 10.5220/0010216806350644