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Full-Text Articles in Physical Sciences and Mathematics

Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea Nov 2015

Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea

Yuliya Lierler

Answer set programming is a declarative programming paradigm oriented towards difficult combinatorial search problems. A fundamental task in answer set programming is to compute stable models, i.e., solutions of logic programs. Answer set solvers are the programs that perform this task. The problem of deciding whether a disjunctive program has a stable model is ΣP2-complete. The high complexity of reasoning within disjunctive logic programming is responsible for few solvers capable of dealing with such programs, namely dlv, gnt, cmodels, clasp and wasp. In this paper, we show that transition systems introduced by Nieuwenhuis, Oliveras, and Tinelli to model and analyze …


Performance Tuning In Answer Set Programming, Matt Buddenhagen, Yuliya Lierler Sep 2015

Performance Tuning In Answer Set Programming, Matt Buddenhagen, Yuliya Lierler

Yuliya Lierler

Performance analysis and tuning are well established software engineering processes in the realm of imperative programming. This work is a step towards establishing the standards of performance analysis in the realm of answer set programming -- a prominent constraint programming paradigm. We present and study the roles of human tuning and automatic configuration tools in this process. The case study takes place in the realm of a real-world answer set programming application that required several hundred lines of code. Experimental results suggest that human-tuning of the logic programming encoding and automatic tuning of the answer set solver are orthogonal (complementary) …


Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman Apr 2015

Prepositional Phrase Attachment Problem Revisited: How Verbnet Can Help, Dan Bailey, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

Resolving attachment ambiguities is a pervasive problem in syntactic analysis. We propose and investigate an approach to resolving prepositional phrase attachment that centers around the ways of incorporating semantic knowledge derived from the lexico-semantic ontologies such as VERBNET and WORDNET.


The Winograd Schema Challenge And Reasoning About Correlation, Dan Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, Julian Michael Dec 2014

The Winograd Schema Challenge And Reasoning About Correlation, Dan Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, Julian Michael

Yuliya Lierler

The Winograd Schema Challenge is an alternative to the Turing Test that may provide a more meaningful measure of machine intelligence. It poses a set of coreference resolution problems that cannot be solved without human-like reasoning. In this paper, we take the view that the solution to such problems lies in establishing discourse coherence. Specifically, we examine two types of rhetorical relations that can be used to establish discourse coherence: positive and negative correlation. We introduce a framework for reasoning about correlation between sentences, and show how this framework can be used to justify solutions to some Winograd Schema problems.


Constraint Answer Set Programming Versus Satisfiability Modulo Theories Or Constraints Versus Theories, Yuliya Lierler, Benjamin Susman Dec 2014

Constraint Answer Set Programming Versus Satisfiability Modulo Theories Or Constraints Versus Theories, Yuliya Lierler, Benjamin Susman

Yuliya Lierler

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. This research direction often informally relates itself to the field of Satisfiability Modulo Theory. Yet the exact formal link is obscured as the terminology and concepts used in these two research fields differ. The goal of this paper to make the link between these two fields precise.