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Predicting program properties such as names or expression types has a wide range of applications. It can ease the task of programming and increase programmer productivity. A major challenge when learning from programs is $\textit{how to…

Programming Languages · Computer Science 2018-04-24 Uri Alon , Meital Zilberstein , Omer Levy , Eran Yahav

Broad application of answer set programming (ASP) for declarative problem solving requires the development of tools supporting the coding process. Program debugging is one of the crucial activities within this process. Recently suggested…

Artificial Intelligence · Computer Science 2014-10-29 Kostyantyn Shchekotykhin

We develop an inductive proof-technique to generate imperative programs for pointer data structures from behavioural specifications expressed in the Answer Set Programming (ASP) formalism. ASP is a non-monotonic logic based formalism that…

Logic in Computer Science · Computer Science 2020-08-14 Sarat Chandra Varanasi , Neeraj Mittal , Gopal Gupta

The Polymorphic Combinatorial Framework (PCF) leverages Large Language Models (LLMs) and mathematical frameworks to guide the meta-prompt enabled design of solution spaces and adaptive AI agents for complex, dynamic environments. Unlike…

Artificial Intelligence · Computer Science 2025-08-05 David Pearl , Matthew Murphy , James Intriligator

Answer Set Programming (ASP) is one of the major declarative programming paradigms in the area of logic programming and non-monotonic reasoning. Despite that ASP features a simple syntax and an intuitive semantics, errors are common during…

Artificial Intelligence · Computer Science 2020-02-19 Carmine Dodaro , Philip Gasteiger , Kristian Reale , Francesco Ricca , Konstantin Schekotihin

GP (for Graph Programs) is a rule-based, nondeterministic programming language for solving graph problems at a high level of abstraction, freeing programmers from handling low-level data structures. The core of GP consists of four…

Logic in Computer Science · Computer Science 2010-04-08 Detlef Plump , Sandra Steinert

Over the past decades, Answer Set Programming (ASP) has emerged as an important paradigm for declarative problem solving. Technological progress in this area has been stimulated by the use of common standards, such as the ASP-Core-2…

Artificial Intelligence · Computer Science 2021-08-10 Kylian Van Dessel , Jo Devriendt , Joost Vennekens

As the practical use of answer set programming (ASP) has grown with the development of efficient solvers, we expect a growing interest in extensions of ASP as their semantics stabilize and solvers supporting them mature. Epistemic…

Artificial Intelligence · Computer Science 2016-10-14 Patrick Thor Kahl , Anthony P. Leclerc , Tran Cao Son

We propose a method for generating explainable rule sets from tree-ensemble learners using Answer Set Programming (ASP). To this end, we adopt a decompositional approach where the split structures of the base decision trees are exploited in…

Artificial Intelligence · Computer Science 2021-09-20 Akihiro Takemura , Katsumi Inoue

This is a preliminary work on configuration knowledge representation which serves as a foundation for building interactive configuration systems in Answer Set programming (ASP). The major concepts of the product configuration problem are…

Artificial Intelligence · Computer Science 2021-09-20 Seemran Mishra

In this paper we propose an extension of Answer Set Programming (ASP), and in particular, of its most general logical counterpart, Quantified Equilibrium Logic (QEL), to deal with partial functions. Although the treatment of equality in QEL…

Logic in Computer Science · Computer Science 2010-06-21 Pedro Cabalar

We propose answer-set programs that specify and compute counterfactual interventions as a basis for causality-based explanations to decisions produced by classification models. They can be applied with black-box models and models that can…

Machine Learning · Computer Science 2020-06-17 Leopoldo Bertossi

In this paper, we present ASPEN, an answer set programming (ASP) implementation of a recently proposed declarative framework for collective entity resolution (ER). While an ASP encoding had been previously suggested, several practical…

This paper explores the use of Answer Set Programming (ASP) in solving Distributed Constraint Optimization Problems (DCOPs). The paper provides the following novel contributions: (1) It shows how one can formulate DCOPs as logic programs;…

Multiagent Systems · Computer Science 2017-05-12 Tiep Le , Tran Cao Son , Enrico Pontelli , William Yeoh

Probabilistic Answer Set Programming under the credal semantics (PASP) extends Answer Set Programming with probabilistic facts that represent uncertain information. The probabilistic facts are discrete with Bernoulli distributions. However,…

Artificial Intelligence · Computer Science 2025-02-19 Damiano Azzolini , Fabrizio Riguzzi

Answer Set Programming (ASP) is a declarative logic formalism that allows to encode computational problems via logic programs. Despite the declarative nature of the formalism, some advanced expertise is required, in general, for designing…

Artificial Intelligence · Computer Science 2020-09-23 Elena Mastria , Jessica Zangari , Simona Perri , Francesco Calimeri

Probabilistic programming is perfectly suited to reliable and transparent data science, as it allows the user to specify their models in a high-level language without worrying about the complexities of how to fit the models. Static analysis…

Artificial Intelligence · Computer Science 2020-08-31 Ryan Bernstein , Matthijs Vákár , Jeannette Wing

Answer Set Programming (ASP) is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, FO(.), PDDL and many others. Since its…

Artificial Intelligence · Computer Science 2020-02-19 Francesco Calimeri , Giovambattista Ianni , Francesco Ricca

Answer Set Programming (ASP) is a well-established declarative paradigm. One of the successes of ASP is the availability of efficient systems. State-of-the-art systems are based on the ground+solve approach. In some applications this…

Artificial Intelligence · Computer Science 2018-02-01 Bernardo Cuteri , Carmine Dodaro , Francesco Ricca , Peter Schüller

We elaborate upon the formal foundations of hybrid Answer Set Programming (ASP) and extend its underlying logical framework with aggregate functions over constraint values and variables. This is achieved by introducing the construct of…

Artificial Intelligence · Computer Science 2020-02-25 Pedro Cabalar , Jorge Fandinno , Torsten Schaub , Philipp Wanko