Abstract
Fuzzy Answer Set Programming (FASP) is an extension of the popular Answer Set Programming (ASP) paradigm which is tailored for continuous domains. Despite the existence of several prototype implementations, none of the existing solvers can handle disjunctive rules in a sound and efficient manner. We first show that a large class of disjunctive FASP programs called the self-reinforcing cycle-free (SRCF) programs can be polynomially reduced to normal FASP programs. We then introduce a general method for solving disjunctive FASP programs, which combines the proposed reduction with the use of mixed integer programming for minimality checking. We also report the result of the experimental benchmark of this method.
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Notes
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The symbol \(\overline{c}\) for a numeric value c represents a truth-value constant in a program.
- 2.
Note that by \(\mathcal {L}\) here, we mean the “set” part of the lattice \(\mathcal {L}\).
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Mushthofa, M., Schockaert, S., De Cock, M. (2015). Solving Disjunctive Fuzzy Answer Set Programs. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science(), vol 9345. Springer, Cham. https://doi.org/10.1007/978-3-319-23264-5_38
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