A Quality Framework for Automated Planning Knowledge Models

Mauro Vallati; Lee McCluskey

doi:10.5220/0010216806350644

A Quality Framework for Automated Planning Knowledge Models

Mauro Vallati, Lee McCluskey

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 13th International Conference on Agents and Artificial Intelligence
Subtitle of host publication	ICAART 2021
Editors	Ana Paula Rocha, Luc Steels, Jaap van den Herik
Publisher	SciTePress
Pages	635-644
Number of pages	10
Volume	2
ISBN (Electronic)	9789897584848
DOIs	https://doi.org/10.5220/0010216806350644
Publication status	Published - 19 Apr 2021
Event	13th International Conference on Agents and Artificial Intelligence - Online due to COVID-19 Duration: 4 Feb 2021 → 6 Feb 2021 Conference number: 13 http://www.icaart.org/Home.aspx

Conference

Conference	13th International Conference on Agents and Artificial Intelligence
Abbreviated title	ICAART 2021
Period	4/02/21 → 6/02/21
Internet address	http://www.icaart.org/Home.aspx

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.5220/0010216806350644Licence: CC BY-NC-ND

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title = "A Quality Framework for Automated Planning Knowledge Models",

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.",

keywords = "Automated planning, Domain models, Knowledge engineering, Quality of models",

author = "Mauro Vallati and Lee McCluskey",

note = "Publisher Copyright: {\textcopyright} 2021 by SCITEPRESS - Science and Technology Publications, Lda. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 13th International Conference on Agents and Artificial Intelligence, ICAART 2021 ; Conference date: 04-02-2021 Through 06-02-2021",

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language = "English",

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editor = "Rocha, {Ana Paula} and Luc Steels and {van den Herik}, Jaap",

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publisher = "SciTePress",

address = "Portugal",

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Vallati, M & McCluskey, L 2021, A Quality Framework for Automated Planning Knowledge Models. in AP Rocha, L Steels & J van den Herik (eds), Proceedings of the 13th International Conference on Agents and Artificial Intelligence: ICAART 2021. vol. 2, SciTePress, pp. 635-644, 13th International Conference on Agents and Artificial Intelligence, 4/02/21. https://doi.org/10.5220/0010216806350644

A Quality Framework for Automated Planning Knowledge Models. / Vallati, Mauro ; McCluskey, Lee.

Proceedings of the 13th International Conference on Agents and Artificial Intelligence: ICAART 2021. ed. / Ana Paula Rocha; Luc Steels; Jaap van den Herik. Vol. 2 SciTePress, 2021. p. 635-644.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Quality Framework for Automated Planning Knowledge Models

AU - Vallati, Mauro

AU - McCluskey, Lee

N1 - Conference code: 13

PY - 2021/4/19

Y1 - 2021/4/19

N2 - 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.

AB - 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.

KW - Automated planning

KW - Domain models

KW - Knowledge engineering

KW - Quality of models

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DO - 10.5220/0010216806350644

M3 - Conference contribution

VL - 2

SP - 635

EP - 644

BT - Proceedings of the 13th International Conference on Agents and Artificial Intelligence

A2 - Rocha, Ana Paula

A2 - Steels, Luc

A2 - van den Herik, Jaap

PB - SciTePress

T2 - 13th International Conference on Agents and Artificial Intelligence

Y2 - 4 February 2021 through 6 February 2021

ER -

A Quality Framework for Automated Planning Knowledge Models

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