48 citations · 174 across the 27 of their papers we have counts for
29 papers
Cplus2ASP: Computing Action Language C+ in Answer Set Programming
Joseph Babb, Joohyung Lee
We present Version 2 of system Cplus2ASP, which implements the definite fragment of action language C+. Its input language is fully compatible with the language of the Causal Calcu…
Weighted Rules under the Stable Model Semantics
Joohyung Lee, Yi Wang
We introduce the concept of weighted rules under the stable model semantics following the log-linear models of Markov Logic. This provides versatile methods to overcome the determi…
Action Language BC+
Joseph Babb, Joohyung Lee
Action languages are formal models of parts of natural language that are designed to describe effects of actions. Many of these languages can be viewed as high level notations of a…
Fuzzy Propositional Formulas under the Stable Model Semantics
Joohyung Lee, Yi Wang
We define a stable model semantics for fuzzy propositional formulas, which generalizes both fuzzy propositional logic and the stable model semantics of classical propositional form…
LPMLN, Weak Constraints, and P-log
Joohyung Lee, Zhun Yang
LPMLN is a recently introduced formalism that extends answer set programs by adopting the log-linear weight scheme of Markov Logic. This paper investigates the relationships betwee…
System ASPMT2SMT:Computing ASPMT Theories by SMT Solvers
Michael Bartholomew, Joohyung Lee
Answer Set Programming Modulo Theories (ASPMT) is an approach to combining answer set programming and satisfiability modulo theories based on the functional stable model semantics.…
Causal Laws and Multi-Valued Fluents
Enrico Giunchiglia, Joohyung Lee, Vladimir Lifschitz +1
This paper continues the line of work on representing properties of actions in nonmonotonic formalisms that stresses the distinction between being "true" and being "caused", as in…
On Loop Formulas with Variables
Joohyung Lee, Yunsong Meng
Recently Ferraris, Lee and Lifschitz proposed a new definition of stable models that does not refer to grounding, which applies to the syntax of arbitrary first-order sentences. We…
First-Order Stable Model Semantics with Intensional Functions
Michael Bartholomew, Joohyung Lee
In classical logic, nonBoolean fluents, such as the location of an object, can be naturally described by functions. However, this is not the case in answer set programs, where the…
Elementary Sets for Logic Programs
Martin Gebser, Joohyung Lee, Yuliya Lierler
By introducing the concepts of a loop and a loop formula, Lin and Zhao showed that the answer sets of a nondisjunctive logic program are exactly the models of its Clark's completio…
Safe Formulas in the General Theory of Stable Models
Joohyung Lee, Vladimir Lifschitz, Ravi Palla
Safe first-order formulas generalize the concept of a safe rule, which plays an important role in the design of answer set solvers. We show that any safe sentence is equivalent, in…
Leveraging Large Language Models to Generate Answer Set Programs
Adam Ishay, Zhun Yang, Joohyung Lee
Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated exceptional performance in various natural language processing tasks and have shown the ability to solve ce…
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text
Zhun Yang, Adam Ishay, Joohyung Lee
While large language models (LLMs), such as GPT-3, appear to be robust and general, their reasoning ability is not at a level to compete with the best models trained for specific n…
Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer
Zhun Yang, Adam Ishay, Joohyung Lee
Constraint satisfaction problems (CSPs) are about finding values of variables that satisfy the given constraints. We show that Transformer extended with recurrence is a viable appr…
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators
Zhun Yang, Joohyung Lee, Chiyoun Park
Injecting discrete logical constraints into neural network learning is one of the main challenges in neuro-symbolic AI. We find that a straight-through-estimator, a method introduc…
An Attention-Based Speaker Naming Method for Online Adaptation in Non-Fixed Scenarios
Jungwoo Pyo, Joohyun Lee, Youngjune Park +2
A speaker naming task, which finds and identifies the active speaker in a certain movie or drama scene, is crucial for dealing with high-level video analysis applications such as a…
Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language
Yi Wang, Shiqi Zhang, Joohyung Lee
To be responsive to dynamically changing real-world environments, an intelligent agent needs to perform complex sequential decision-making tasks that are often guided by commonsens…
Explainable Fact Checking with Probabilistic Answer Set Programming
Naser Ahmadi, Joohyung Lee, Paolo Papotti +1
One challenge in fact checking is the ability to improve the transparency of the decision. We present a fact checking method that uses reference information in knowledge graphs (KG…
Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+
Yi Wang, Joohyung Lee
We extend probabilistic action language pBC+ with the notion of utility as in decision theory. The semantics of the extended pBC+ can be defined as a shorthand notation for a decis…
Weight Learning in a Probabilistic Extension of Answer Set Programs
Joohyung Lee, Yi Wang
LPMLN is a probabilistic extension of answer set programs with the weight scheme derived from that of Markov Logic. Previous work has shown how inference in LPMLN can be achieved.…
Translating LPOD and CR-Prolog2 into Standard Answer Set Programs
Joohyung Lee, Zhun Yang
Logic Programs with Ordered Disjunction (LPOD) is an extension of standard answer set programs to handle preference using the construct of ordered disjunction, and CR-Prolog2 is an…
A Probabilistic Extension of Action Language BC+
Joohyung Lee, Yi Wang
We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the propose…
Representing Hybrid Automata by Action Language Modulo Theories
Joohyung Lee, Nikhil Loney, Yunsong Meng
Both hybrid automata and action languages are formalisms for describing the evolution of dynamic systems. This paper establishes a formal relationship between them. We show how to…
Computing LPMLN Using ASP and MLN Solvers
Joohyung Lee, Samidh Talsania, Yi Wang
LPMLN is a recent addition to probabilistic logic programming languages. Its main idea is to overcome the rigid nature of the stable model semantics by assigning a weight to each r…