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The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of…

人工智能 · 计算机科学 2018-08-23 Michael Gelfond , Yuanlin Zhang

The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of…

人工智能 · 计算机科学 2020-02-19 Michael Gelfond , Yuanlin Zhang

The paper continues the investigation of Poincare and Russel's Vicious Circle Principle (VCP) in the context of the design of logic programming languages with sets. We expand previously introduced language Alog with aggregates by allowing…

人工智能 · 计算机科学 2016-08-31 Michael Gelfond , Yuanlin Zhang

In this paper, we propose a variant of Answer Set Programming (ASP) with evaluable functions that extends their application to sets of objects, something that allows a fully logical treatment of aggregates. Formally, we start from the…

人工智能 · 计算机科学 2018-05-03 Pedro Cabalar , Jorge Fandinno , Luis Fariñas del Cerro , David Pearce

Aggregates provide a concise way to express complex knowledge. The problem of selecting an appropriate formalisation of aggregates for answer set programming (ASP) remains unsettled. This paper revisits it from the viewpoint of…

人工智能 · 计算机科学 2022-05-18 Linde Vanbesien , Maurice Bruynooghe , Marc Denecker

Weight constraint and aggregate programs are among the most widely used logic programs with constraints. In this paper, we relate the semantics of these two classes of programs, namely the stable model semantics for weight constraint…

计算机科学中的逻辑 · 计算机科学 2011-05-18 Guohua Liu , Jia-Huai You

Answer Set Programming (ASP) is logic programming under the stable model or answer set semantics. During the last decade, this paradigm has seen several extensions by generalizing the notion of atom used in these programs. Among these,…

人工智能 · 计算机科学 2014-05-07 Mario Alviano , Wolfgang Faber

Complex reasoning problems are most clearly and easily specified using logical rules, but require recursive rules with aggregation such as count and sum for practical applications. Unfortunately, the meaning of such rules has been a…

数据库 · 计算机科学 2023-08-29 Yanhong A. Liu , Scott D. Stoller

Answer Set Programming (ASP) emerged in the late 1990ies as a paradigm for Knowledge Representation and Reasoning. The attractiveness of ASP builds on an expressive high-level modeling language along with the availability of powerful…

人工智能 · 计算机科学 2021-09-20 Mario Alviano , Wolfgang Faber , Martin Gebser

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not…

人工智能 · 计算机科学 2012-03-19 Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir

Answer set programming (ASP) is a logic programming paradigm that can be used to solve complex combinatorial search problems. Aggregates are an ASP construct that plays an important role in many applications. Defining a satisfactory…

人工智能 · 计算机科学 2008-12-09 Paolo Ferraris

Over the last decades the development of ASP has brought about an expressive modeling language powered by highly performant systems. At the same time, it gets more and more difficult to provide semantic underpinnings capturing the resulting…

人工智能 · 计算机科学 2021-08-09 Pedro Cabalar , Jorge Fandinno , Torsten Schaub , Philipp Wanko

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…

人工智能 · 计算机科学 2026-03-09 Yann Munro , Isabelle Bloch , Marie-Jeanne Lesot

Answer Set Programming (ASP) is a well-known problem-solving formalism in computational logic. Nowadays, ASP is used in many real world scenarios thanks to ASP solvers. Standard evaluation of ASP programs suffers from an intrinsic…

计算机科学中的逻辑 · 计算机科学 2021-09-20 Giuseppe Mazzotta

In recent years, Answer Set Programming (ASP), logic programming under the stable model or answer set semantics, has seen several extensions by generalizing the notion of an atom in these programs: be it aggregate atoms, HEX atoms,…

人工智能 · 计算机科学 2013-12-23 Mario Alviano , Wolfgang Faber

Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucination problem. While Uncertainty Quantification (UQ) is essential for assessing reliability,…

计算与语言 · 计算机科学 2026-04-15 Guanran Luo , Wentao Qiu , Wanru Zhao , Wenhan Lv , Zhongquan Jian , Meihong Wang , Qingqiang Wu

The paper presents two equivalent definitions of answer sets for logic programs with aggregates. These definitions build on the notion of unfolding of aggregates, and they are aimed at creating methodologies to translate logic programs with…

软件工程 · 计算机科学 2007-05-23 Tran Cao Son , Enrico Pontelli , Islam Elkabani

Weighted knowledge bases for description logics with typicality under a "concept-wise" multi-preferential semantics provide a logical interpretation of MultiLayer Perceptrons. In this context, Answer Set Programming (ASP) has been shown to…

人工智能 · 计算机科学 2023-03-28 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

We propose a stable model semantics for higher-order logic programs. Our semantics is developed using Approximation Fixpoint Theory (AFT), a powerful formalism that has successfully been used to give meaning to diverse non-monotonic…

计算机科学中的逻辑 · 计算机科学 2025-01-22 Bart Bogaerts , Angelos Charalambidis , Giannos Chatziagapis , Babis Kostopoulos , Samuele Pollaci , Panos Rondogiannis

Word puzzles and the problem of their representations in logic languages have received considerable attention in the last decade (Ponnuru et al. 2004; Shapiro 2011; Baral and Dzifcak 2012; Schwitter 2013). Of special interest is the problem…

人工智能 · 计算机科学 2016-08-08 Tiantian Gao , Paul Fodor , Michael Kifer
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