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Over the last couple of decades, there has been a considerable effort devoted to the problem of updating logic programs under the stable model semantics (a.k.a. answer-set programs) or, in other words, the problem of characterising the…

Artificial Intelligence · Computer Science 2022-02-22 João Leite , Martin Slota

Free monads (and their variants) have become a popular general-purpose tool for representing the semantics of effectful programs in proof assistants. These data structures support the compositional definition of semantics parameterized by…

Programming Languages · Computer Science 2022-07-28 Yao Li , Stephanie Weirich

This paper describes a system, called PLP, for compiling ordered logic programs into standard logic programs under the answer set semantics. In an ordered logic program, rules are named by unique terms, and preferences among rules are given…

Artificial Intelligence · Computer Science 2007-05-23 James P. Delgrande , Torsten Schaub , Hans Tompits

This paper shows that the semantics of programs with aggregates implemented by the solvers clingo and dlv can be characterized as extended First-Order formulas with intensional functions in the logic of Here-and-There. Furthermore, this…

Artificial Intelligence · Computer Science 2024-12-17 Jorge Fandinno , Zachary Hansen

The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models. In this manuscript, we propose an extractor-paraphraser based abstractive summarization system…

Computation and Language · Computer Science 2021-05-05 Anubhav Jangra , Raghav Jain , Vaibhav Mavi , Sriparna Saha , Pushpak Bhattacharyya

Reductions combine collections of inputs with an associative (and here, also commutative) operator to produce collections of outputs. When the same value contributes to multiple outputs, there is an opportunity to reuse partial results,…

Programming Languages · Computer Science 2024-11-27 Louis Narmour , Ryan Job , Tomofumi Yuki , Sanjay Rajopadhye

Answer set programming (ASP) is a paradigm for declarative problem solving where problems are first formalized as rule sets, i.e., answer-set programs, in a uniform way and then solved by computing answer sets for programs. The…

Artificial Intelligence · Computer Science 2011-08-31 Mai Nguyen , Tomi Janhunen , Ilkka Niemelä

Human annotations are vital to supervised learning, yet annotators often disagree on the correct label, especially as annotation tasks increase in complexity. A strategy to improve label quality is to ask multiple annotators to label the…

Machine Learning · Computer Science 2023-12-22 Alexander Braylan , Madalyn Marabella , Omar Alonso , Matthew Lease

Answer set programming (ASP) is a popular declarative programming paradigm with various applications. Programs can easily have many answer sets that cannot be enumerated in practice, but counting still allows quantifying solution spaces. If…

Artificial Intelligence · Computer Science 2023-11-14 Johannes K. Fichte , Sarah Alice Gaggl , Markus Hecher , Dominik Rusovac

An abstract argumentation framework can be used to model the argumentative stance of an agent at a high level of abstraction, by indicating for every pair of arguments that is being considered in a debate whether the first attacks the…

Artificial Intelligence · Computer Science 2017-07-28 Weiwei Chen , Ulle Endriss

This article contains a proposal to add coinduction to the computational apparatus of natural language understanding. This, we argue, will provide a basis for more realistic, computationally sound, and scalable models of natural language…

Computation and Language · Computer Science 2020-12-11 Wlodek W. Zadrozny

The state of the art on many NLP tasks is currently achieved by large pre-trained language models, which require a considerable amount of computation. We explore a setting where many different predictions are made on a single piece of text.…

Computation and Language · Computer Science 2020-04-30 Jingfei Du , Myle Ott , Haoran Li , Xing Zhou , Veselin Stoyanov

Answer Set Programming (ASP) is a purely declarative formalism developed in the field of logic programming and nonmonotonic reasoning: computational problems are encoded by logic programs whose answer sets, corresponding to solutions, are…

Artificial Intelligence · Computer Science 2020-02-19 Francesco Calimeri , Simona Perri , Jessica Zangari

Learning on sets is increasingly gaining attention in the machine learning community, due to its widespread applicability. Typically, representations over sets are computed by using fixed aggregation functions such as sum or maximum.…

Machine Learning · Computer Science 2021-06-07 Giovanni Pellegrini , Alessandro Tibo , Paolo Frasconi , Andrea Passerini , Manfred Jaeger

Interpolation is an important property of classical and many non-classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the the non-monotonic system of…

Logic in Computer Science · Computer Science 2014-01-17 Dov Gabbay , David Pearce , Agustín Valverde

Logic programs, more specifically, Answer-set programs, can be annotated with probabilities on facts to express uncertainty. We address the problem of propagating weight annotations on facts (eg probabilities) of an ASP to its standard…

Logic in Computer Science · Computer Science 2025-03-31 Francisco Coelho , Bruno Dinis , Dietmar Seipel , Salvador Abreu

Formal argumentation is being used increasingly in artificial intelligence as an effective and understandable way to model potentially conflicting pieces of information, called arguments, and identify so-called acceptable arguments…

Artificial Intelligence · Computer Science 2026-03-09 Yann Munro , Isabelle Bloch , Marie-Jeanne Lesot

Answer Set Programming (ASP) is an important logic programming paradigm within the field of Knowledge Representation and Reasoning. As a concise, human-readable, declarative language, ASP is an excellent tool for developing trustworthy…

Logic in Computer Science · Computer Science 2025-02-14 Zachary Hansen

We consider a Reinforcement Learning setup where an agent interacts with an environment in observation-reward-action cycles without any (esp.\ MDP) assumptions on the environment. State aggregation and more generally feature reinforcement…

Artificial Intelligence · Computer Science 2014-07-15 Marcus Hutter

Extending the lambda-calculus with a construct for sharing, such as let expressions, enables a special representation of terms: iterated applications are decomposed by introducing sharing points in between any two of them, reducing to the…

Logic in Computer Science · Computer Science 2019-07-16 Beniamino Accattoli , Andrea Condoluci , Giulio Guerrieri , Claudio Sacerdoti Coen
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