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  • Cited by 7
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    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Di Rosa, Emanuele Giunchiglia, Enrico and Maratea, Marco 2010. Solving satisfiability problems with preferences. Constraints, Vol. 15, Issue. 4, p. 485.


    Zhao, Lingzhong Qian, Junyan Chang, Liang and Cai, Guoyong 2010. Using ASP for knowledge management with user authorization. Data & Knowledge Engineering, Vol. 69, Issue. 8, p. 737.


    Costantini, Stefania and Formisano, Andrea 2009. Modeling preferences and conditional preferences on resource consumption and production in ASP. Journal of Algorithms, Vol. 64, Issue. 1, p. 3.


    Pulka, Andrzej 2009. 2009 2nd Conference on Human System Interactions. p. 32.

    Flores-Bazán, Fabián Hernández, Elvira and Novo, Vicente 2008. Characterizing efficiency without linear structure: a unified approach. Journal of Global Optimization, Vol. 41, Issue. 1, p. 43.


    Van Nieuwenborgh, Davy De Cock, Martine and Vermeir, Dirk 2007. An introduction to fuzzy answer set programming. Annals of Mathematics and Artificial Intelligence, Vol. 50, Issue. 3-4, p. 363.


    Jones, James D. 2006. A different paradigm for expert systems: an introduction to logic programming and related knowledge representation issues. Expert Systems, Vol. 23, Issue. 5, p. 342.


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Preferred answer sets for ordered logic programs

  • DAVY VAN NIEUWENBORGH (a1) and DIRK VERMEIR (a1)
  • DOI: http://dx.doi.org/10.1017/S1471068404002315
  • Published online: 01 January 2006
Abstract

We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a “best” answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibly at the cost of violating less important ones. We show that such a rule order induces a natural order on extended answer sets, the minimal elements of which we call preferred answer sets. We characterize the expressiveness of the resulting semantics and show that it can simulate negation as failure, disjunction and some other formalisms such as logic programs with ordered disjunction. The approach is shown to be useful in several application areas, e.g. repairing database, where minimal repairs correspond to preferred answer sets.

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Theory and Practice of Logic Programming
  • ISSN: 1471-0684
  • EISSN: 1475-3081
  • URL: /core/journals/theory-and-practice-of-logic-programming
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