Results 1 - 10 of 395

The DLV System for Knowledge Representation and Reasoning

by Nicola Leone, Gerald Pfeifer, Wolfgang Faber, Thomas Eiter, Georg Gottlob, Simona Perri, Francesco Scarcello - 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 ..."
Abstract - Cited by 455 (102 self) - Add to MetaCart
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 (disjunction-free) 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 state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free 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 3-complete problems) in a declarative fashion. On the foundational side, we provide a detailed analysis of the computational complexity of the language of

clasp: A conflict-driven answer set solver

by Martin Gebser, Benjamin Kaufmann, André Neumann, Torsten Schaub - In LPNMR’07 , 2007
"... Abstract. We describe the conflict-driven answer set solver clasp, whichis based on concepts from constraint processing (CSP) and satisfiability checking (SAT). We detail its system architecture and major features, and provide a systematic empirical evaluation of its features. 1 ..."
Abstract - Cited by 107 (9 self) - Add to MetaCart
Abstract. We describe the conflict-driven answer set solver clasp, whichis based on concepts from constraint processing (CSP) and satisfiability checking (SAT). We detail its system architecture and major features, and provide a systematic empirical evaluation of its features. 1
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A uniform integration of higher-order reasoning and external evaluations in answer-set programming

by Thomas Eiter, Giovambattista Ianni, Roman Schindlauer, Hans Tompits - In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI-05 , 2005
"... We introduce HEX programs, which are nonmonotonic logic programs admitting higher-order atoms as well as external atoms, and we extend the wellknown answer-set semantics to this class of programs. Higher-order features are widely acknowledged as useful for performing meta-reasoning, among other task ..."
Abstract - Cited by 98 (41 self) - Add to MetaCart
We introduce HEX programs, which are nonmonotonic logic programs admitting higher-order atoms as well as external atoms, and we extend the wellknown answer-set semantics to this class of programs. Higher-order features are widely acknowledged as useful for performing meta-reasoning, among other tasks. Furthermore, the possibility to exchange knowledge with external sources in a fully declarative framework such as Answer-Set Programming (ASP) is nowadays important, in particular in view of applications in the Semantic Web area. Through external atoms, HEX programs can model some important extensions to ASP, and are a useful KR tool for expressing various applications. Finally, complexity and implementation issues for a preliminary prototype are discussed. 1

Logic Programming and Knowledge Representation - the A-Prolog perspective

by Michael Gelfond, Nicola Leone - 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 ..."
Abstract - Cited by 98 (2 self) - Add to MetaCart
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 well-founded semantics, general theories of argumentation, abductive reasoning, etc., the reader is referred to other publications.
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Probabilistic reasoning with answer sets

by Chitta Baral, Michael Gelfond, Nelson Rushton - In Proceedings of LPNMR-7 , 2004
"... Abstract. We give a logic programming based account of probability and describe a declarative language P-log capable of reasoning which combines both logical and probabilistic arguments. Several non-trivial examples illustrate the use of P-log for knowledge representation. 1 ..."
Abstract - Cited by 91 (11 self) - Add to MetaCart
Abstract. We give a logic programming based account of probability and describe a declarative language P-log capable of reasoning which combines both logical and probabilistic arguments. Several non-trivial examples illustrate the use of P-log for knowledge representation. 1
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Consistent Query Answering: Five Easy Pieces

by Jan Chomicki , 2007
"... Consistent query answering (CQA) is an approach to querying inconsistent databases without repairing them first. This invited talk introduces the basics of CQA, and discusses selected issues in this area. The talk concludes with a summary of other relevant work and an outline of potential future r ..."
Abstract - Cited by 81 (3 self) - Add to MetaCart
Consistent query answering (CQA) is an approach to querying inconsistent databases without repairing them first. This invited talk introduces the basics of CQA, and discusses selected issues in this area. The talk concludes with a summary of other relevant work and an outline of potential future research topics.

Ultimate Well-founded and Stable Semantics for Logic Programs With Aggregates (Extended Abstract)

by Marc Denecker, Nikolay Pelov, Maurice Bruynooghe - In Proceedings of ICLP-01, LNCS 2237 , 2001
"... is relatively straightforward. Another advantage of the ultimate approximation is that in cases where TP is monotone the ultimate well-founded model will be 2-valued and will coincide with the least fixpoint of TP . This is not the case for the standard well-founded semantics. For example in the sta ..."
Abstract - Cited by 63 (10 self) - Add to MetaCart
is relatively straightforward. Another advantage of the ultimate approximation is that in cases where TP is monotone the ultimate well-founded model will be 2-valued and will coincide with the least fixpoint of TP . This is not the case for the standard well-founded semantics. For example in the standard well-founded model of the program: # p. p. p is undefined while the associated TP operator is monotone and p is true in the ultimate well-founded model. One disadvantage of using the ultimate semantics is that it has a higher computational cost even for programs without aggregates. The complexity goes one level higher in the polynomial hierarchy to # 2 for the well-founded model and to 2 for a stable model which is also complete for this class [2]. Fortunately, by adding aggregates the complexity does not increase further. To give an example of a logic program with aggregates we consider the problem of computing the length of the shortest path between two nodes in a direc
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Answer Sets

by Michael Gelfond , 2007
"... This chapter is an introduction to Answer Set Prolog- a language for knowledge representation and reasoning based on the answer set/stable model semantics of logic programs [44, 45]. The language has roots in declarative programing [52, 65], the syntax and semantics of standard Prolog [24, 23], disj ..."
Abstract - Cited by 61 (5 self) - Add to MetaCart
This chapter is an introduction to Answer Set Prolog- a language for knowledge representation and reasoning based on the answer set/stable model semantics of logic programs [44, 45]. The language has roots in declarative programing [52, 65], the syntax and semantics of standard Prolog [24, 23], disjunctive databases [66, 67] and nonmonotonic logic

Constraint Answer Set Solving

by Martin Gebser, Max Ostrowski, Torsten Schaub
"... Abstract. We present a new approach to integrating Constraint Processing (CP) techniques into Answer Set Programming (ASP). Based on an alternative semantic approach, we develop an algorithmic framework for conflict-driven ASP solving that exploits CP solving capacities. A significant technical issu ..."
Abstract - Cited by 50 (8 self) - Add to MetaCart
Abstract. We present a new approach to integrating Constraint Processing (CP) techniques into Answer Set Programming (ASP). Based on an alternative semantic approach, we develop an algorithmic framework for conflict-driven ASP solving that exploits CP solving capacities. A significant technical issue concerns the combination of conflict information from different solver types. We have implemented our approach, combining ASP solver clingo with the generic CP solver gecode, and we empirically investigate its computational impact. 1
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Answer set optimization

by Gerhard Brewka, Ilkka Niemela, Miroslaw Truszczynski - PROC. IJCAI-03 , 2003
"... We investigate the combination of answer set programming and qualitative optimization techniques. Answer set optimization programs (ASO programs) have two parts. The generating program produces answer sets representing possible solutions. The preference program expresses user preferences. It induces ..."
Abstract - Cited by 49 (10 self) - Add to MetaCart
We investigate the combination of answer set programming and qualitative optimization techniques. Answer set optimization programs (ASO programs) have two parts. The generating program produces answer sets representing possible solutions. The preference program expresses user preferences. It induces a preference relation on the answer sets of based on the degree to which rules are satisfied. We discuss possible applications of ASO programming, give complexity results and propose implementation techniques. We also analyze the relationship between A SO programs and CP-networks.