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73
The DLV System for Knowledge Representation and Reasoning
 ACM Transactions on Computational Logic
, 2002
"... Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge representation and reasoning, which is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class ΣP 2 (NPNP). Thus, under widely believ ..."
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Cited by 455 (102 self)
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Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge representation and reasoning, which is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class ΣP 2 (NPNP). Thus, under widely believed assumptions, DLP is strictly more expressive than normal (disjunctionfree) logic programming, whose expressiveness is limited to properties decidable in NP. Importantly, apart from enlarging the class of applications which can be encoded in the language, disjunction often allows for representing problems of lower complexity in a simpler and more natural fashion. This paper presents the DLV system, which is widely considered the stateoftheart implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, functionfree disjunctive logic programs (also known as disjunctive datalog), extended by weak constraints, which are a powerful tool to express optimization problems. We then illustrate the usage of DLV as a tool for knowledge representation and reasoning, describing a new declarative programming methodology which allows one to encode complex problems (up to ∆P 3complete problems) in a declarative fashion. On the foundational side, we provide a detailed analysis of the computational complexity of the language of
Stable models and an alternative logic programming paradigm
 In The Logic Programming Paradigm: a 25Year Perspective
, 1999
"... In this paper we reexamine the place and role of stable model semantics in logic programming and contrast it with a least Herbrand model approach to Horn programs. We demonstrate that inherent features of stable model semantics naturally lead to a logic programming system that offers an interesting ..."
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Cited by 309 (19 self)
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In this paper we reexamine the place and role of stable model semantics in logic programming and contrast it with a least Herbrand model approach to Horn programs. We demonstrate that inherent features of stable model semantics naturally lead to a logic programming system that offers an interesting alternative to more traditional logic programming styles of Horn logic programming, stratified logic programming and logic programming with wellfounded semantics. The proposed approach is based on the interpretation of program clauses as constraints. In this setting programs do not describe a single intended model, but a family of stable models. These stable models encode solutions to the constraint satisfaction problem described by the program. Our approach imposes restrictions on the syntax of logic programs. In particular, function symbols are eliminated from the language. We argue that the resulting logic programming system is wellattuned to problems in the class NP, has a welldefined domain of applications, and an emerging methodology of programming. We point out that what makes the whole approach viable is recent progress in implementations of algorithms to compute stable models of propositional logic programs. 1
Smodels  an Implementation of the Stable Model and WellFounded Semantics for Normal Logic Programs
, 1997
"... The Smodels system is a C++ implementation of the wellfounded and stable model semantics for rangerestricted functionfree normal programs. The system includes two modules: (i) smodels which implements the two semantics for ground programs and (ii) parse which computes a grounded version of a range ..."
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Cited by 293 (9 self)
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The Smodels system is a C++ implementation of the wellfounded and stable model semantics for rangerestricted functionfree normal programs. The system includes two modules: (i) smodels which implements the two semantics for ground programs and (ii) parse which computes a grounded version of a rangerestricted functionfree normal program. The latter module does not produce the whole set of ground instances of the program but a subset that is sufficient in the sense that no stable models are lost. The implementation of the stable model semantics for ground programs is based on bottomup backtracking search where a powerful pruning method is employed. The pruning method exploits an approximation technique for stable models which is closely related to the wellfounded semantics. One of the advantages of this novel technique is that it can be implemented to work in linear space. This makes it possible to apply the stable model semantics also in areas where resulting programs are highly n...
The KR System dlv: Progress Report, Comparisons and Benchmarks
, 1998
"... dlv is a knowledge representation system, based on disjunctive logic programming, which offers frontends to several advanced KR formalisms. The system has ..."
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Cited by 120 (23 self)
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dlv is a knowledge representation system, based on disjunctive logic programming, which offers frontends to several advanced KR formalisms. The system has
Logic Programming and Knowledge Representation  the AProlog perspective
 Artificial Intelligence
, 2002
"... In this paper we give a short introduction to logic programming approach to knowledge representation and reasoning. The intention is to help the reader to develop a 'feel' for the field's history and some of its recent developments. The discussion is mainly limited to logic programs u ..."
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Cited by 98 (2 self)
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In this paper we give a short introduction to logic programming approach to knowledge representation and reasoning. The intention is to help the reader to develop a 'feel' for the field's history and some of its recent developments. The discussion is mainly limited to logic programs under the answer set semantics. For understanding of approaches to logic programming build on wellfounded semantics, general theories of argumentation, abductive reasoning, etc., the reader is referred to other publications.
Reasoning Agents In Dynamic Domains
 In Workshop on LogicBased Artificial Intelligence
, 2000
"... The paper discusses an architecture for intelligent agents based on the use of AProlog  a language of logic programs under the answer set semantics. AProlog is used to represent the agent's knowledge about the domain and to formulate the agent's reasoning tasks. We outline how these ta ..."
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Cited by 90 (28 self)
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The paper discusses an architecture for intelligent agents based on the use of AProlog  a language of logic programs under the answer set semantics. AProlog is used to represent the agent's knowledge about the domain and to formulate the agent's reasoning tasks. We outline how these tasks can be reduced to answering questions about properties of simple logic programs and demonstrate the methodology of constructing these programs. Keywords: Intelligent agents, logic programming and nonmonotonic reasoning. 1 INTRODUCTION This paper is a report on the attempt by the authors to better understand the design of software components of intelligent agents capable of reasoning, planning and acting in a changing environment. The class of such agents includes, but is not limited to, intelligent mobile robots, softbots, immobots, intelligent information systems, expert systems, and decisionmaking systems. The ability to design intelligent agents (IA) is crucial for such diverse tasks as ...
An AProlog decision support system for the Space Shuttle
 In PADL 2001
, 2000
"... The goal of this paper is to test if a programming methodology based on the declarative language AProlog, algorithms for computing answer sets of programs of AProlog, and programming systems implementing these algorithms can be successfully applied to the development of medium size knowledge ..."
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Cited by 81 (17 self)
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The goal of this paper is to test if a programming methodology based on the declarative language AProlog, algorithms for computing answer sets of programs of AProlog, and programming systems implementing these algorithms can be successfully applied to the development of medium size knowledgeintensive applications. We report on a successful design and development of such a system controlling some of the functions of the Space Shuttle. Introduction The research presented in this paper is rooted in recent developments in several areas of AI. Advances in the work on semantics of negation in logic programming (Gelfond & Lifschitz 1988; 1991) and on formalization of commonsense reasoning (Reiter 1980; Moore 1985) led to the development of the declarative language, AProlog, used in this paper to encode the domain knowledge, and to an AProlog based methodology for representing defaults. Insights on the nature of causality and its relationship with answer sets of logic programs (...
Solving Advanced Reasoning Tasks using Quantified Boolean Formulas
, 2000
"... We consider the compilation of different reasoning tasks into the evaluation problem of quantified boolean formulas (QBFs) as an approach to develop prototype reasoning systems useful, e.g., for experimental purposes. ..."
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Cited by 72 (20 self)
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We consider the compilation of different reasoning tasks into the evaluation problem of quantified boolean formulas (QBFs) as an approach to develop prototype reasoning systems useful, e.g., for experimental purposes.