On Using Action Inheritance and Modularity in PDDL Domain Modelling

Alan Lindsay

doi:10.1609/icaps.v33i1.27203

On Using Action Inheritance and Modularity in PDDL Domain Modelling

Alan Lindsay^*

^*Corresponding author for this work

School of Mathematical & Computer Sciences

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

4 Citations (Scopus)

Abstract

The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.

Original language	English
Title of host publication	Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling
Pages	259-267
Number of pages	9
Volume	33
Edition	1
DOIs	https://doi.org/10.1609/icaps.v33i1.27203
Publication status	Published - 1 Jul 2023
Event	33rd International Conference on Automated Planning and Scheduling 2023 - Prague, Czech Republic Duration: 8 Jul 2023 → 13 Jul 2023

Conference

Conference	33rd International Conference on Automated Planning and Scheduling 2023
Abbreviated title	ICAPS 2023
Country/Territory	Czech Republic
City	Prague
Period	8/07/23 → 13/07/23

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems and Management

Access to Document

10.1609/icaps.v33i1.27203

Cite this

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title = "On Using Action Inheritance and Modularity in PDDL Domain Modelling",

abstract = "The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.",

author = "Alan Lindsay",

note = "Funding Information: The authors wish to acknowledge the SSHRC-UKRI Canada-UK Artificial Intelligence Initiative (UKRI grant ES/T01296/1) for financial support of this work. Publisher Copyright: Copyright {\textcopyright} 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 33rd International Conference on Automated Planning and Scheduling 2023, ICAPS 2023 ; Conference date: 08-07-2023 Through 13-07-2023",

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N2 - The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.

AB - The PDDL modelling problem is known to be challenging, time consuming and error prone. This has led researchers to investigate methods of supporting the modelling process. One particular avenue is to adapt tools and techniques that have proven useful in software engineering to support the modelling process. We observe that concepts, such as inheritance and modularity have not been fully explored in the context of modelling PDDL planning models. Within software engineering these concepts help to organise and provide structure to code, which can make it easier to read, debug, and reuse code. In this work we consider inheritance and modularity and their use in PDDL action descriptions, and how these can have a similar impact on the PDDL modelling process. We define an extension to PDDL and develop appropriate tools to compile models using these extensions, both directly from the command line and through the Visual Studio Code PDDL extension. We report on our use of inheritance and modularity when modelling a planning model for a companion robot scenario. We also discuss the benefits of exploiting the inheritance hierarchy in other modules within our robot system.

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ER -

On Using Action Inheritance and Modularity in PDDL Domain Modelling

Abstract

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