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research-article

On using action inheritance and modularity in PDDL domain modelling

AUTHOR:

Alan LindsayAuthors Info & Claims

ICAPS '23: Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling

Article No.: 32, Pages 259 - 267

https://doi.org/10.1609/icaps.v33i1.27203

Published: 08 July 2023 Publication History

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.

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Cited By

Lindsay ARamírez-Duque APetrick RFoster M(2024)A Socially Assistive Robot using Automated Planning in a Paediatric Clinical SettingProceedings of the 2024 International Symposium on Technological Advances in Human-Robot Interaction10.1145/3648536.3648542(47-55)Online publication date: 9-Mar-2024
https://dl.acm.org/doi/10.1145/3648536.3648542
Lindsay ARamirez Duque AFoster MPetrick RGrollman DBroadbent EJu WSoh HWilliams T(2024)Using AI Planning for Managing Affective States in Social RoboticsCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640744(679-683)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640744

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Published In

cover image Guide Proceedings

ICAPS '23: Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling

July 2023

685 pages

ISBN:1-57735-881-3

Copyright © 2023 Association for the Advancement of Artificial Intelligence.

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National Science Foundation (NSF)
Artificial Intelligence Journal
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Sony AI
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AAAI Press

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Published: 08 July 2023

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Cited By

Lindsay ARamírez-Duque APetrick RFoster M(2024)A Socially Assistive Robot using Automated Planning in a Paediatric Clinical SettingProceedings of the 2024 International Symposium on Technological Advances in Human-Robot Interaction10.1145/3648536.3648542(47-55)Online publication date: 9-Mar-2024
https://dl.acm.org/doi/10.1145/3648536.3648542
Lindsay ARamirez Duque AFoster MPetrick RGrollman DBroadbent EJu WSoh HWilliams T(2024)Using AI Planning for Managing Affective States in Social RoboticsCompanion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3610978.3640744(679-683)Online publication date: 11-Mar-2024
https://dl.acm.org/doi/10.1145/3610978.3640744

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