162,832 research outputs found
Normal forms for Answer Sets Programming
Normal forms for logic programs under stable/answer set semantics are
introduced. We argue that these forms can simplify the study of program
properties, mainly consistency. The first normal form, called the {\em kernel}
of the program, is useful for studying existence and number of answer sets. A
kernel program is composed of the atoms which are undefined in the Well-founded
semantics, which are those that directly affect the existence of answer sets.
The body of rules is composed of negative literals only. Thus, the kernel form
tends to be significantly more compact than other formulations. Also, it is
possible to check consistency of kernel programs in terms of colorings of the
Extended Dependency Graph program representation which we previously developed.
The second normal form is called {\em 3-kernel.} A 3-kernel program is composed
of the atoms which are undefined in the Well-founded semantics. Rules in
3-kernel programs have at most two conditions, and each rule either belongs to
a cycle, or defines a connection between cycles. 3-kernel programs may have
positive conditions. The 3-kernel normal form is very useful for the static
analysis of program consistency, i.e., the syntactic characterization of
existence of answer sets. This result can be obtained thanks to a novel
graph-like representation of programs, called Cycle Graph which presented in
the companion article \cite{Cos04b}.Comment: 15 pages, To appear in Theory and Practice of Logic Programming
(TPLP
Rewriting recursive aggregates in answer set programming: back to monotonicity
Aggregation functions are widely used in answer set programming for representing and reasoning on knowledge involving sets of objects collectively. Current implementations simplify the structure of programs in order to optimize the overall performance. In particular, aggregates are rewritten into simpler forms known as monotone aggregates. Since the evaluation of normal programs with monotone aggregates is in general on a lower complexity level than the evaluation of normal programs with arbitrary aggregates, any faithful translation function must introduce disjunction in rule heads in some cases. However, no function of this kind is known. The paper closes this gap by introducing a polynomial, faithful, and modular translation for rewriting common aggregation functions into the simpler form accepted by current solvers. A prototype system allows for experimenting with arbitrary recursive aggregates, which are also supported in the recent version 4.5 of the grounder gringo, using the methods presented in this paper
A finite-valued solver for disjunctive fuzzy answer set programs
Fuzzy Answer Set Programming (FASP) is a declarative programming paradigm which extends the flexibility and expressiveness of classical Answer Set Programming (ASP), with the aim of modeling continuous application domains. In contrast to the availability of efficient ASP solvers, there have been few attempts at implementing FASP solvers. In this paper, we propose an implementation of FASP based on a reduction to classical ASP. We also develop a prototype implementation of this method. To the best of our knowledge, this is the first solver for disjunctive FASP programs. Moreover, we experimentally show that our solver performs well in comparison to an existing solver (under reasonable assumptions) for the more restrictive class of normal FASP programs
Modeling Stable Matching Problems with Answer Set Programming
The Stable Marriage Problem (SMP) is a well-known matching problem first
introduced and solved by Gale and Shapley (1962). Several variants and
extensions to this problem have since been investigated to cover a wider set of
applications. Each time a new variant is considered, however, a new algorithm
needs to be developed and implemented. As an alternative, in this paper we
propose an encoding of the SMP using Answer Set Programming (ASP). Our encoding
can easily be extended and adapted to the needs of specific applications. As an
illustration we show how stable matchings can be found when individuals may
designate unacceptable partners and ties between preferences are allowed.
Subsequently, we show how our ASP based encoding naturally allows us to select
specific stable matchings which are optimal according to a given criterion.
Each time, we can rely on generic and efficient off-the-shelf answer set
solvers to find (optimal) stable matchings.Comment: 26 page
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