Externally Supported Models for Efficient Computation of Paracoherent Answer Sets


  • Giovanni Amendola University of Calabria
  • Carmine Dodaro University of Genova
  • Wolfgang Faber University of Huddersfield
  • Francesco Ricca University of Calabria




Knowledge Representation and Reasoning, Answer Set Programming, Paracoherent Answer Sets


Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning.While incoherence, the non-existence of answer sets for some programs, is an important feature of ASP, it has frequently been criticised and indeed has some disadvantages, especially for query answering.Paracoherent semantics have been suggested as a remedy, which extend the classical notion of answer sets to draw meaningful conclusions also from incoherent programs. In this paper we present an alternative characterization of the two major paracoherent semantics in terms of (extended) externally supported models. This definition uses a transformation of ASP programs that is more parsimonious than the classic epistemic transformation used in recent implementations.A performance comparison carried out on benchmarks from ASP competitions shows that the usage of the new transformation brings about performance improvements that are independent of the underlying algorithms.




How to Cite

Amendola, G., Dodaro, C., Faber, W., & Ricca, F. (2018). Externally Supported Models for Efficient Computation of Paracoherent Answer Sets. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11540



AAAI Technical Track: Knowledge Representation and Reasoning