Propositional abduction is almost always hard

  • Authors:
  • Gustav Nordh;Bruno Zanuttini

  • Affiliations:
  • Dept. of Computer & Information Science, Linkööpings Universitet, Linköping, Sweden;GREYC, UMR, CNRS, Université de Caen, Caen Cedex, France

  • Venue:
  • IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
  • Year:
  • 2005

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Abstract

Abduction is a fundamental form of nonmonotonic reasoning that aims at finding explanations for observed manifestations. Applications of this process range from car configuration to medical diagnosis. We study here its computational complexity in the case where the application domain is described by a propositional theory built upon a fixed constraint language and the hypotheses and manifestations are described by sets of literals. We show that depending on the language the problem is either polynomial-time solvable, NP-complete, or ΣP2-complete. In particular, we show that under the assumption P≠NP, only languages that are affine of width 2 have a polynomial algorithm, and we exhibit very weak conditions for NP-hardness.