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Analysing AI Planning Problems in Linear Logic – A Partial Deduction Approach

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Advances in Artificial Intelligence – SBIA 2004 (SBIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3171))

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Abstract

This article presents a framework for analysing AI planning problem specifications. We consider AI planning as linear logic (LL) theorem proving. Then the usage of partial deduction is proposed as a foundation of an analysis technique for AI planning problems, which are described in LL. By applying this technique we are able to investigate for instance why there is no solution for a particular planning problem.

We consider here !-Horn fragment of LL, which is expressive enough for representing STRIPS-like planning problems. Anyway, by taking advantage of full LL, more expressive planning problems can be described, Therefore, the framework proposed here could be seen as a step towards analysing both, STRIPS-like and more complex planning problems.

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Authors and Affiliations

  1. Department of Computer and Information Science, Norwegian University of Science and Technology,  

    Peep Küngas

Authors
  1. Peep Küngas
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Editors and Affiliations

  1. Instituto de Informática, UFRGS, Porto Alegre, RS, Brasil

    Ana L. C. Bazzan

  2. Intelligent Systems Laboratory LSI, Center of Technology, Federal University of Maranao UFMA, Bacanga Campus, 65080-040, Sao Luis, MA, Brazil

    Sofiane Labidi

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Küngas, P. (2004). Analysing AI Planning Problems in Linear Logic – A Partial Deduction Approach. In: Bazzan, A.L.C., Labidi, S. (eds) Advances in Artificial Intelligence – SBIA 2004. SBIA 2004. Lecture Notes in Computer Science(), vol 3171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28645-5_6

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  • DOI: https://doi.org/10.1007/978-3-540-28645-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23237-7

  • Online ISBN: 978-3-540-28645-5

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