On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts

Authors

  • Éric Grégoire CRIL Université d'Artois
  • Yacine Izza CRIL Université d'Artois
  • Jean-Marie Lagniez CRIL Université d'Artois

DOI:

https://doi.org/10.1609/aaai.v30i1.10431

Keywords:

MSS, Co-MSS, MCS, SAT, satisfiability reasoning, reasoning under contexts

Abstract

The efficient extraction of one maximal information subset that does not conflict with multiple contxts or additional information sources is a key basic issue in many A.I. domains, especially when these contexts or sources can be mutually conflicting. In this paper, this question is addressed from a computational point of view in clausal Boolean logic. A new approach is introduced that experimentally outperforms the currently most efficient technique.

AAAI 2016 Proceedings Cover

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Published

2016-03-05

How to Cite

Grégoire, Éric, Izza, Y., & Lagniez, J.-M. (2016). On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.10431

Issue

Vol. 30 No. 1 (2016): Thirtieth AAAI Conference on Artificial Intelligence

Section

Technical Papers: Search and Constraint Satisfaction