Model-based Planning in Physical domains using SetGraphs

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Garagnani, M.. 2004. Model-based Planning in Physical domains using SetGraphs. In: Frans Coenen; Alun Preece and Ann L. Macintosh, eds. Research and Development in Intelligent Systems XX: Proceedings of AI2003, the Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. London: Springer, pp. 295-308. ISBN 9781852337803 [Book Section]

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Official URL: https://link.springer.com/chapter/10.1007/978-0-85...

Abstract or Description

This paper proposes a non-propositional representation framework for planning in physical domains. Physical planning problems involve identifying a correct sequence (plan) of object manipulations, transformations and spatial rearrangements to achieve an assigned goal. The problem of the ramification of action effects causes most current (propositional) planning languages to have inefficient encodings of physical domains. A simpler and more efficient representation is proposed, in which actions, goals and world state are modelled using ‘setGraphs’. A setGraph is an abstract data-structure able to capture implicitly the structural and
topological constraints of a physical domain. Despite being model-based, the representation also allows the use of types and propositional furmulæ to specify additional domain constraints. Experimental results obtained with a specific implementation of the representation indicate significant improvements in performance in all of the domains considered.

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Book Section

Identification Number (DOI):

https://doi.org/10.1007/978-0-85729-412-8_22