NDLI: Weight constraint programs with evaluable functions

Content Provider	Springer Nature Link
Author	Zhang, Mingyi You, Jia Huai Yuan, Li Yan Wang, Yisong Lin, Fangzhen
Copyright Year	2011
Abstract	In the current practice of Answer Set Programming (ASP), evaluable functions are represented as special kinds of relations. This often makes the resulting program unnecessarily large when instantiated over a large domain. The extra constraints needed to enforce the relation as a function also make the logic program less transparent. In this paper, we consider adding evaluable functions to answer set logic programs. The class of logic programs that we consider here is that of weight constraint programs, which are widely used in ASP. We propose an answer set semantics to these extended weight constraint programs and define loop completion to characterize the semantics. Computationally, we provide a translation from loop completions of these programs to instances of the Constraint Satisfaction Problem (CSP) and use the off-the-shelf CSP solvers to compute the answer sets of these programs. A main advantage of this approach is that global constraints implemented in such CSP solvers become available to ASP. The approach also provides a new encoding for CSP problems in the style of weight constraint programs. We have implemented a prototype system based on these results, and our experiments show that this prototype system competes well with the state-of-the-art ASP solvers. In addition, we illustrate the utilities of global constraints in the ASP context.
Ending Page	380
Page Count	40
Starting Page	341
File Format	PDF
ISSN	10122443
e-ISSN	15737470
Journal	Annals of Mathematics and Artificial Intelligence
Issue Number	3-4
Volume Number	60
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-06-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Constraint satisfaction problem Weight constraints Problem solving (heuristics, search strategies, etc.) Logic in artificial intelligence Answer set programming Knowledge representation Computer Science Artificial Intelligence (incl. Robotics) Evaluable functions Mathematics Statistical Physics, Dynamical Systems and Complexity
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence

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