SelectedWorks - Yuliya Lierler

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Selected Works of Yuliya Lierler

Cheryl Prewett Diamond Associate Professor

Dr. Yuliya Lierler joined the Computer Science Department in the College of Information Science & Technology (IS&T) at the University of Nebraska at Omaha in 2012. She is now at the rank of the full professor. In September 2020, she has been appointed to the Cheryl Prewett Diamond Professorship. In 2024, she has been awarded an Outstanding Research and Creativity Award by the College of IS&T affirming her exemplary contributions to research. Dr. Lierler’s research interests and contributions are within the field of artificial intelligence, especially in the area of knowledge representation, automated reasoning, declarative problem solving, and natural language understanding. In 2020, she was elected as an Executive Committee member of the Association of Logic Programming. Prior to coming to UNO, Dr. Lierler was a Computing Innovation Fellow Postdoc at the University of Kentucky. She holds a Ph.D. in Computer Sciences from the University of Texas at Austin.

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About Yuliya Lierler

Dr. Yuliya Lierler joined the Computer Science Department in the College of Information Science & Technology (IS&T) at the University of Nebraska at Omaha in 2012. She is now at the rank of the full professor. In September 2020, she has been appointed to the Cheryl Prewett Diamond Professorship. In 2024, she has been awarded an Outstanding Research and Creativity Award by the College of IS&T affirming her exemplary contributions to research. Dr. Lierler’s research interests and contributions are within the field of artificial intelligence, especially in the area of knowledge representation, automated reasoning, declarative problem solving, and natural language understanding. In 2020, she was elected as an Executive Committee member of the Association of Logic Programming. Prior to coming to UNO, Dr. Lierler was a Computing Innovation Fellow Postdoc at the University of Kentucky. She holds a Ph.D. in Computer Sciences from the University of Texas at Austin.

Discrete Mathematics in a Nutshell or Theoretical Foundations of Computer Science (Yuliya Lierler) (2024)

This textbook on Theoretical Foundations of Computer Science has been largely inspired by the style of teaching practiced by Vladimir Lifschitz during my years at the University of Theoretical Foundations of Computer Science Texas at Austin. ...

Basics behind Answer Sets (Yuliya Lierler) Topics in AI: Knowledge Representation and Reasoning (2020)

Answer Set Programming Paradigm (Yuliya Lierler) Topics in AI: Knowledge Representation and Reasoning (2020)

Algorithms in Backtracking Search behind SAT and ASP (Yuliya Lierler) Topics in AI: Knowledge Representation and Reasoning (2020)

SM-based Semantics for Answer Set Programs Containing Conditional Literals and Arithmetic (long version) (Zachary Hansen and Yuliya Lierler) Proceedings of the 27th International Symposium on Practical Aspects of Declarative Languages (2025)

Modern answer set programming solvers such as CLINGO support advanced language constructs that improve the expressivity and conciseness of logic programs. Conditional literals are one such construct. They form “subformulas” that behave as nested implications ...

tExplain: Information Extraction with Explanations (Pedro Cabalar, Adrian Dorsey, Jorge Fandinno, et al.) Proceedings of the 17th International Conference on Logic Programming and Non-monotonic Reasoning (2024)

We present a narrative understanding tool that takes as an input a narrative in natural English language that contains both sentences describing actions as well as questions and outputs answers to those questions together with ...

An Abstract View on Optimizations in Propositional Frameworks (Yuliya Lierler) Annals of Mathematics and Artificial Intelligence (2024)

Search-optimization problems are plentiful in scientific and engineering domains. Artificial intelligence has long contributed to the development of search algorithms and declarative programming languages geared towards solving and modelings search-optimization problems. Automated reasoning and knowledge ...

Axiomatization of Non-Recursive Aggregates in First-Order Answer Set Programming (Jorge Fandinno, Zachary Hansen and Yuliya Lierler) Journal of Artificial Intelligence Research (2024)

This paper contributes to the development of theoretical foundations of answer set programming. Groundbreaking work on the SM operator by Ferraris, Lee, and Lifschitz proposed a definition/semantics for logic (answer set) programs based on a ...

Historical Review of Variants of Informal Semantics for Logic Programs under Answer Set Semantics: GL’88, GL’91, GK’14, D-V’12 (Yuliya Lierler) Theory and Practice of Logic Programming (2024)

This note presents a historical survey of informal semantics that are associated with logic programming under answer set semantics. We review these in uniform terms and align them with two paradigms: Answer Set Programming and ...

Information Extraction Tool TEXT2ALM: From Narratives to Action Language System Descriptions and Query Answering (Yuliya Lierler, Gang Ling and Craig Olson) AI communications (2024)

System Predictor: Grounding Size Estimator for Logic Programs under Answer Set Semantics (Daniel Bresnahan, Nicholas Hippen and Yuliya Lierler) Theory and Practice of Logic Programming (2024)

Answer set programming is a declarative logic programming paradigm geared towards solving difficult combinatorial search problems. While different logic programs can encode the same problem, their performance may vary significantly. It is not always easy ...

Splitting Answer Set Programs with respect to Intensionality Statements (Jorge Fandinno and Yuliya Lierler) AAAI (2023)

Splitting a logic program allows us to reduce the task of computing its stable models to similar tasks for its subprograms. This can be used to increase solving performance and to prove the correctness of ...

Constraint Answer Set Programming: Integrational and Translational (or SMT-based) Approaches (Yuliya Lierler) Theory and Practice of Logic Programming (2023)

Constraint answer set programming or CASP, for short, is a hybrid approach in automated reasoning putting together the advances of distinct research areas such as answer set programming, constraint processing, and satisfiability modulo theories. Constraint ...

External Behavior of a Logic Program and Verification of Refactoring (Jorge Fandinno, Zachary Hansen, Yuliya Lierler, et al.) Theory and Practice of Logic Programming (2023)

Refactoring is modifying a program without changing its external behavior. In this paper, we make the concept of external behavior precise for a simple answer set programming language. Then we describe a proof assistant for ...

Unifying Framework for Optimizations in non-boolean Formalisms (Yuliya Lierler) Theory and Practice of Logic Programming (2023)

Search-optimization problems are plentiful in scientific and engineering domains. Artificial intelligence has long contributed to the development of search algorithms and declarative programming languages geared towards solving and modeling search-optimization problems. Automated reasoning and knowledge ...

Axiomatization of Aggregates in Answer Set Programming (Jorge Fandinno, Zach Hansen and Yuliya Lierler) 36th AAAI Conference on Artificial Intelligence (2022)

The paper presents a characterization of logic programs with aggregates based on a many-sorted generalization of operator SM that refers neither to grounding nor to fixpoints. This characterization introduces new function symbols for aggregate operations and ...

A Machine Learning System to Improve the Performance of ASP Solving Based on Encoding Selection (Liu Liu, Miroslaw Truszczyński and Yuliya Lierler) Proceedings of the 16th International Conference on Logic Programming and Non-monotonic Reasoning (2022)

Answer set programming (ASP) has long been used for modeling and solving hard search problems. Experience shows that the performance of ASP tools on different ASP encodings of the same problem may vary greatly from ...

Arguing Correctness of ASP Programs with Aggregates (Jorge Fandinno, Zachary Hansen and Yuliya Lierler) Proceedings of the 16th International Conference on Logic Programming and Non-monotonic Reasoning (2022)

This paper studies the problem of arguing program correctness for logic programs with aggregates in the context of Answer Set Programming. Cabalar, Fandinno, and Lierler (2020) championed a modular methodology for arguing program correctness. We ...

Semantics for Conditional Literals via the SM Operator (Zachary Hansen and Yuliya Lierler) Proceedings of the 16th International Conference on Logic Programming and Non-monotonic Reasoning (2022)

Conditional literals are an expressive Answer Set Programming language construct supported by the solver Clingo. Their semantics are currently defined by a translation to infinitary propositional logic, however, we develop an alternative characterization with the ...

Strong Equivalence and Program Structure in Arguing Essential Equivalence between Logic Programs (Yuliya Lierler) Theory and Practice of Logic Programming (2022)

Answer set programming is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing different knowledge representation formalisms. Frequently, several related and yet substantially different answer set programs exist for a given ...

An Abstract View on Optimizations in SAT and ASP (Yuliya Lierler) Proceedings of the 17th European Conference on Logics in Artificial Intelligence (JELIA), Austria (2021)

Search-optimization problems are plentiful in scientific and engineering domains. MaxSAT and answer set programming with weak constraints (ASPWC) are popular frameworks for modeling and solving search problems with optimization criteria. There is a solid understanding ...

DualGrounder: Lazy Instantiation via Clingo Multi-shot Framework (Justin Robbins and Yuliya Lierler) Proceedings of the 17th European Conference on Logics in Artificial Intelligence (JELIA), Austria (2021)

Answer set programming (ASP) is a declarative programming paradigm that is geared towards difficult combinatorial search problems. Sometimes, run times of ASP systems suffer due to so called grounding bottleneck. Lazy grounding solvers aim to ...

Estimating Grounding Sizes of Logic Programs under Answer Set Semantics (Nicholas Hippen and Yuliya Lierler) Proceedings of the 17th European Conference on Logics in Artificial Intelligence (JELIA), Austria (2021)

Answer set programming (ASP) is a declarative logic programming paradigm geared towards solving difficult combinatorial search problems. While different logic programs can encode the same problem, their performance may vary significantly. It is not always ...

Information Extraction Tool Text2Alm: From Narratives to Action Language System Descriptions (Extended Abstract) (Yuliya Lierler) 18th International Conference on Principles of Knowledge Representation and Reasoning (Recently Published Research Track) (2021)

Unifying Framework for Optimizations in CASP; SMT; ILP (Yuliya Lierler) (2021)

Search-optimization problems are plentiful in scientific and engineering domains. Many popular automated reasoning paradigms provide users with languages supporting optimization statements. Recall integer linear programming, MaxSAT, optimization satisfiability modulo theory, (constraint) answer set programming. These ...