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Full-Text Articles in Physical Sciences and Mathematics
Model Generation For Generalized Quantifiers Via Answer Set Programming, Yuliya Lierler, Günther Görz
Model Generation For Generalized Quantifiers Via Answer Set Programming, Yuliya Lierler, Günther Görz
Computer Science Faculty Proceedings & Presentations
For the semantic evaluation of natural language sentences, in particular those containing generalized quantifiers, we subscribe to the generate and test methodology to produce models of such sentences. These models are considered as means by which the sentences can be interpreted within a natural language processing system. The goal of this paper is to demonstrate that answer set programming is a simple, efficient and particularly well suited model generation technique for this purpose, leading to a straightforward implementation.
Experiments With Sat-Based Answer Set Programming, Enrico Giunchiglia, Yuliya Lierler, Marco Maratea, A. Tacchella
Experiments With Sat-Based Answer Set Programming, Enrico Giunchiglia, Yuliya Lierler, Marco Maratea, A. Tacchella
Computer Science Faculty Proceedings & Presentations
Answer Set Programming (ASP) emerged in the late 1990s as a new logic programming paradigm which has been successfully applied in various application domains. Propositional satisfiability (SAT) is one of the most studied problems in Computer Science. ASP and SAT are closely related: Recent works have studied their relation, and efficient SAT-based ASP solvers (like assat and Cmodels) exist. In this paper we report about (i) the extension of the basic procedures in Cmodels in order to incorporate the most popular SAT reasoning strategies, and (ii) an extensive comparative analysis involving also other state-of-the-art answer set solvers. The experimental analysis …