Abstraction Within Partial Deduction for Linear Logic

  • Peep Küngas
Conference paper

DOI: 10.1007/978-3-540-30210-0_6

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3249)
Cite this paper as:
Küngas P. (2004) Abstraction Within Partial Deduction for Linear Logic. In: Buchberger B., Campbell J. (eds) Artificial Intelligence and Symbolic Computation. AISC 2004. Lecture Notes in Computer Science, vol 3249. Springer, Berlin, Heidelberg

Abstract

Abstraction has been used extensively in Artificial Intelligence (AI) planning, human problem solving and theorem proving. In this article we show how to apply abstraction within Partial Deduction (PD) formalism for Linear Logic (LL). The proposal is accompanied with formal results identifying limitations and advantages of the approach.

We adapt a technique from AI planning for constructing abstraction hierarchies, which are then exploited during PD. Although the complexity of PD for propositional LL is generally decidable, by applying abstraction the complexity is reduced to polynomial in certain cases.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Peep Küngas
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and Technology 

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