System Projector: An Automatic Program Rewriting Tool For Non-Ground Answer Set Programs, Yuliya Lierler
Aug 2019
System Projector: An Automatic Program Rewriting Tool For Non-Ground Answer Set Programs, Yuliya Lierler
Yuliya Lierler
Answer set programming is a popular constraint programming paradigm that has seen wide use across various industry applications. However, logic programs under answer set semantics often require careful design and nontrivial expertise from a programmer to obtain satisfactory solving times. In order to reduce this burden on a software engineer we propose an automated rewriting technique for non-ground logic programs that we implement in a system PROJECTOR. We conduct rigorous experimental analysis, which shows that applying system PROJECTOR to a logic program can improve its performance, even after significant human-performed optimizations. This talk will present PROJECTOR and considered experimental analysis …
Information Extraction Tool Text2alm: From Narratives To Action Language System Descriptions, Craig Olson, Yuliya Lierler
Aug 2019
Information Extraction Tool Text2alm: From Narratives To Action Language System Descriptions, Craig Olson, Yuliya Lierler
Yuliya Lierler
In this work we design a narrative understanding tool Text2Alm. System Text2Alm uses an action language ALM to perform inferences on complex interactions of events described in narratives. The methodology used to implement the Text2Alm was originally outlined by Lierler et al. 2017 via a manual process of converting a narrative to an ALM model. It relies on a conglomeration of resources and techniques from two distinct fields of artificial intelligence, namely, natural language processing and knowledge representation and reasoning. The effectiveness of system Text2Alm is measured by its ability to correctly answer questions from the bAbI tasks published by …
Plw Tutorial: Processing Narratives By Means Of Action Languages, Yuliya Lierler
Jun 2019
Plw Tutorial: Processing Narratives By Means Of Action Languages, Yuliya Lierler
Yuliya Lierler
The tutorial explains the design of a narrative understanding tool Text2Alm. System Text2Alm uses an action language ALM to perform inferences on complex interactions of events described in narratives. The methodology used to implement the Text2Alm was originally outlined by Lierler, Inclezan, and Gelfond in 2017. Text2Alm relies on a conglomeration of resources and techniques from two distinct fields of artificial intelligence, namely, natural language processing and knowledge representation and reasoning. The tutorial will also present the results on the effectiveness of system Text2Alm measured by its ability to correctly answer questions from the bAbI tasks published by Facebook Research …
Automatic Program Rewriting In Non-Ground Answer Set Programs, Yuliya Lierler
Jan 2019
Automatic Program Rewriting In Non-Ground Answer Set Programs, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Automatic Program Rewriting In Non-Ground Answer Set Programs, Nicholas Hippen, Yuliya Lierler
Dec 2018
Automatic Program Rewriting In Non-Ground Answer Set Programs, Nicholas Hippen, Yuliya Lierler
Yuliya Lierler
Answer set programming is a popular constraint programming paradigm that has seen wide use across various industry applications. However, logic programs under answer set semantics often require careful design and nontrivial expertise from a programmer to obtain satisfactory solving times. In order to reduce this burden on a software engineer we propose an automated rewriting technique for non-ground logic programs that we implement in a system Projector. We conduct rigorous experimental analysis, which shows that applying system Projector to a logic program can improve its performance, even after significant human-performed optimizations.
Strong Equivalence And Program's Structure In Arguing Essential Equivalence Between First-Order Logic Programs, Yuliya Lierler
Dec 2018
Strong Equivalence And Program's Structure In Arguing Essential Equivalence Between First-Order Logic Programs, Yuliya Lierler
Yuliya Lierler
Answer set programming is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing distinct knowledge representation formalisms. It is common that several related and yet substantially different answer set programs exist for a given problem. Sometimes these encodings may display significantly different performance. Uncovering precise formal links between these programs is often important and yet far from trivial. This paper claims the correctness of a number of interesting program rewritings. Notably, they assume programs with variables and such important language features as choice, disjunction, and aggregates. We showcase the utility of some considered rewritings by using …
Smt-Based Constraint Answer Set Solver Ezsmt+ For Non-Tight Programs, Da Shen, Yuliya Lierler
Sep 2018
Smt-Based Constraint Answer Set Solver Ezsmt+ For Non-Tight Programs, Da Shen, Yuliya Lierler
Yuliya Lierler
Constraint answer set programming integrates answer set programming with constraint processing. System Ezsmt+ is a constraint answer set programming tool that utilizes satisfiability modulo theory solvers for search. The truly unique feature of ezsmt+ is its capability to process linear as well as nonlinear constraints simultaneously containing integer and real variables.
Smt-Based Constraint Answer Set Solver Ezsmt, Yuliya Lierler
Sep 2018
Smt-Based Constraint Answer Set Solver Ezsmt, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Strong Equivalence And Conservative Extensions Hand In Hand For Arguing Correctness Of New Action Language C Formalization, Yuliya Lierler
Aug 2018
Strong Equivalence And Conservative Extensions Hand In Hand For Arguing Correctness Of New Action Language C Formalization, Yuliya Lierler
Yuliya Lierler
Answer set programming is a declarative programming paradigm used in formulating combinatorial search problems and implementing distinct knowledge representation and reasoning formalisms. It is common that several related and yet substantially different answer set programs exist for a given problem. Uncovering precise formal links between these programs is often of value. This paper develops a methodology for establishing such links. This methodology relies on the notions of strong equivalence and conservative extensions and a body of earlier theoretical work related to these concepts. We use distinct answer set programming formalizations of an action language C and a syntactically restricted action …
Smt-Based Answer Set Solver Cmodels-Diff (System Description), Da Shen, Yuliya Lierler
Jun 2018
Smt-Based Answer Set Solver Cmodels-Diff (System Description), Da Shen, Yuliya Lierler
Yuliya Lierler
Many answer set solvers utilize Satisfiability solvers for search. SMT solvers extend Satisfiability solvers. This paper presents the CMODELS-DIFF system that uses SMT solvers to find answer sets of a logic program. Its theoretical foundation is based on Niemala's characterization of answer sets of a logic program via so called level rankings. The comparative experimental analysis demonstrates that CMODELS-DIFF is a viable answer set solver.
Basics Behind Answer Sets, Yuliya Lierler
Jul 2017
Basics Behind Answer Sets, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Answer Set Programming Paradigm, Yuliya Lierler
Jun 2017
Answer Set Programming Paradigm, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Algorithms In Backtracking Search Behind Sat And Asp, Yuliya Lierler
Feb 2017
Algorithms In Backtracking Search Behind Sat And Asp, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Syllabus: Csci 3450: Natural Language Processing, Yuliya Lierler
Dec 2016
Syllabus: Csci 3450: Natural Language Processing, Yuliya Lierler
Yuliya Lierler
No abstract provided.
First-Order Modular Logic Programs And Their Conservative Extensions (Extended Abstract), Amelia Harrison, Yuliya Lierler
Dec 2016
First-Order Modular Logic Programs And Their Conservative Extensions (Extended Abstract), Amelia Harrison, Yuliya Lierler
Yuliya Lierler
This paper introduces first-order modular logic programs, which provide a way of viewing answer set programs as consisting of many independent, meaningful modules. We also present conservative extensions of such programs. This concept helps to identify strong relationships between modular programs as well as between traditional programs. For example, we illustrate how the notion of a conservative extension can be used to justify the common projection rewriting. This is a short version of a paper that appeared at the 32nd International Conference on Logic Programming.
Syllabus: Csci8010: Advanced Topics In Artificial Intelligence, Yuliya Lierler
Dec 2016
Syllabus: Csci8010: Advanced Topics In Artificial Intelligence, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Action Languages And Question Answering, Yuliya Lierler, Daniela Inclezan, Michael Gelfond
Dec 2016
Action Languages And Question Answering, Yuliya Lierler, Daniela Inclezan, Michael Gelfond
Yuliya Lierler
This paper describes a methodology for designing Question Answering systems that utilize an action language ALM to allow inferences based on complex interactions of events described in texts. This methodology assumes the extension of the VERBNET lexicon with interpretable semantic annotations in ALM and specifies the use of several other NLP resources to produce ALM system descriptions for input discourses.
Syllabus: Csci 8450 Advanced Topics In Natural Language Understanding, Yuliya Lierler
Dec 2016
Syllabus: Csci 8450 Advanced Topics In Natural Language Understanding, Yuliya Lierler
Yuliya Lierler
No abstract provided.
What Is Answer Set Programming To Propositional Satisfiability, Yuliya Lierler
Nov 2016
What Is Answer Set Programming To Propositional Satisfiability, Yuliya Lierler
Yuliya Lierler
Propositional satisfiability (or satisfiability) and answer set programming are two closely related subareas of Artificial Intelligence that are used to model and solve difficult combinatorial search problems. Satisfiability solvers and answer set solvers are the software systems that find satisfying interpretations and answer sets for given propositional formulas and logic programs, respectively. These systems are closely related in their common design patterns. In satisfiability, a propositional formula is used to encode problem specifications in a way that its satisfying interpretations correspond to the solutions of the problem. To find solutions to a problem it is then sufficient to use a …
Constraint Cnf: A Sat And Csp Language Under One Roof, Broes De Cat, Yuliya Lierler
Sep 2016
Constraint Cnf: A Sat And Csp Language Under One Roof, Broes De Cat, Yuliya Lierler
Yuliya Lierler
A new language, called constraint CNF, is proposed. It integrates propositional logic with constraints stemming from constraint programming (CP). A family of algorithms is designed to solve problems expressed in constraint CNF. These algorithms build on techniques from both propositional satisfiability (SAT) and CP. The result is a uniform language and an algorithmic framework, which allow us to gain a deeper understanding of the relation between the solving techniques used in SAT and in CP and apply them together.
Constraint Answer Set Programming Versus Satisfiability Modulo Theories, Yuliya Lierler, Benjamin Susman
Jun 2016
Constraint Answer Set Programming Versus Satisfiability Modulo Theories, Yuliya Lierler, Benjamin Susman
Yuliya Lierler
Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of Satisfiability Modulo Theories. Yet, the exact formal link is obscured as the terminology and concepts used in these two research areas differ. In this paper, we make the link between these two areas precise.
Iclp Tutorial: Relating Constraint Answer Set Programming And Satisfiability Modulo Theories, Yuliya Lierler
Dec 2015
Iclp Tutorial: Relating Constraint Answer Set Programming And Satisfiability Modulo Theories, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Syllabus: Csci2030: Mathematical Foundations Of Computer Science, Yuliya Lierler
Dec 2015
Syllabus: Csci2030: Mathematical Foundations Of Computer Science, Yuliya Lierler
Yuliya Lierler
No abstract provided.
Systems, Engineering Environments, And Competitions, Yuliya Lierler, Marco Maratea, Francesco Ricca
Dec 2015
Systems, Engineering Environments, And Competitions, Yuliya Lierler, Marco Maratea, Francesco Ricca
Yuliya Lierler
The goal of this paper is threefold. First, we trace the history of the development of answer set solvers, by accounting for more than a dozen of them. Second, we discuss development tools and environments that facilitate the use of answer set programming technology in practical applications. Last, we present the evolution of the answer set programming competitions, prime venues for tracking advances in answer set solving technology.
Elements Of Discrete Mathematics, Yuliya Lierler
Dec 2015
Elements Of Discrete Mathematics, Yuliya Lierler
Yuliya Lierler
No abstract provided.
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.
