In answer-set programming (ASP), the main focus usually is on computing answer sets which correspond to solutions to the problem represented by a logic program. Simple reasoning over answer sets is sometimes supported...
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the proceedings contain 6 papers. the topics discussed include: on building a competitive comformant planner;a preference meta-model for logic programs with possibilistic ordered disjunction;a framework for programmin...
the proceedings contain 6 papers. the topics discussed include: on building a competitive comformant planner;a preference meta-model for logic programs with possibilistic ordered disjunction;a framework for programming with module consequences;a pragmatic programmer's guide for answer set programming;yet another modular action language;and a visual tracer for DLV.
the proceedings contain 65 papers. the topics discussed include: logic-based modeling in systems biology;integrating answer set programming and satisfiability modulo theories;splitting a CR-prolog pro;contextual argum...
ISBN:
(纸本)3642042376
the proceedings contain 65 papers. the topics discussed include: logic-based modeling in systems biology;integrating answer set programming and satisfiability modulo theories;splitting a CR-prolog pro;contextual argumentation in ambient intelligence;argumentation context systems: a framework for abstract group argumentation;a revised concept of safety for general answer set programs;magic sets for the bottom-up evaluation of finitely recursive programs;relevance-driven evaluation of modular nonmonotoniclogic programs;complexity of the stable model semantics for queries on incomplete databases;manifold answer-set programs for meta-reasoning;computing stable models through reductions to difference logic;module-based framework for multi-language constraint modeling;and induction on failure: learning connected horn theories.
the need for integration of ontologies withnonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantic...
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the need for integration of ontologies withnonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics for hybrid knowledge bases composed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. these semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve. In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties. To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.
the need for integration of ontologies withnonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantic...
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the need for integration of ontologies withnonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics for hybrid knowledge bases composed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. these semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve. In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties. To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.
In this paper, we propose the logic P min , which is a nonmonotonic extension of Preferential logic P defined by Kraus, Lehmann and Magidor (KLM). In order to perform nonmonotonic inferences, we define a "minimal...
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We present a novel approach to non-monotonic ILP and its implementation called TAL (Top-directed Abductive Learning). TAL overcomes some of the completeness problems of ILP systems based on Inverse Entailment and is t...
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ISBN:
(纸本)9783939897170
We present a novel approach to non-monotonic ILP and its implementation called TAL (Top-directed Abductive Learning). TAL overcomes some of the completeness problems of ILP systems based on Inverse Entailment and is the first top-down ILP system that allows background theories and hypotheses to be normal logic programs. the approach relies on mapping an ILP problem into an equivalent ALP one. this enables the use of established ALP proof procedures and the specification of richer language bias with integrity constraints. the mapping provides a principled search space for an ILP problem, over which an abductive search is used to compute inductive solutions.
the proceedings contain 45 papers. the special focus in this conference is on logic for programming, Artificial Intelligence, and reasoning. the topics include: Characterising space complexity classes via Knuth-Bendix...
ISBN:
(纸本)9783642162411
the proceedings contain 45 papers. the special focus in this conference is on logic for programming, Artificial Intelligence, and reasoning. the topics include: Characterising space complexity classes via Knuth-Bendix orders;focused natural deduction;how to universally close the existential rule;on the Complexity of the Bernays-Schönfinkel Class with Datalog;magically constraining the inverse method using dynamic polarity assignment;lazy abstraction for size-change termination;a syntactical approach to qualitative constraint networks merging;on the satisfiability of two-variable logic over data words;generic methods for formalising sequent calculi applied to provability logic;awareness in games, awareness in logic;characterising probabilistic processes logically: (Extended abstract);fCube: An efficient prover for Intuitionistic propositional logic;superposition-Based Analysis of First-Order Probabilistic Timed Automata;A nonmonotonic extension of KLM Preferential logic P;on strong normalization of the Calculus of Constructions with type-based termination;aligators for arrays (tool paper);Clause elimination procedures for CNF formulas;Partitioning SAT instances for distributed solving;infinite families of finite string rewriting systems and their confluence;polite theories revisited;human and unhuman commonsense reasoning;clausal graph tableaux for hybrid logic with eventualities and difference;the consistency of the CADIAG-2 knowledge base: A probabilistic approach;on the Complexity of Model Expansion;labelled Unit Superposition Calculi for Instantiation-Based reasoning;Boosting local search thanks to CDCL;interpolating quantifier-free Presburger Arithmetic;variable compression in ProbLog;Improving resource-unaware SAT solvers;expansion nets: Proof-nets for propositional classical logic;revisiting matrix interpretations for polynomial derivational complexity of term rewriting;Gödel logics – A SURVEY;bottom-up tree automata with term constraints.
reasoning under fuzzy uncertainty arises in many applications including planning and scheduling in fuzzy environments. In many real-world applications, it is necessary to define fuzzy uncertainty over qualitative unce...
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ISBN:
(纸本)9783642159503
reasoning under fuzzy uncertainty arises in many applications including planning and scheduling in fuzzy environments. In many real-world applications, it is necessary to define fuzzy uncertainty over qualitative uncertainty, where fuzzy values are assigned over the possible outcomes of qualitative uncertainty. However, current fuzzy logicprogramming frameworks support only reasoning under fuzzy uncertainty. Moreover, disjunctive logic programs, although used for reasoning under qualitative uncertainty it cannot be used for reasoning with fuzzy uncertainty. In this paper we combine extended and normal fuzzy logic programs [30, 23], for reasoning under fuzzy uncertainty, with disjunctive logic programs [7, 4], for reasoning under qualitative uncertainty, in a unified logicprogramming framework, namely extended and normal disjunctive fuzzy logic programs. this is to allow directly and intuitively to represent and reason in the presence of both fuzzy uncertainty and qualitative uncertainty. the syntax and semantics of extended and normal disjunctive fuzzy logic programs naturally extends and subsumes the syntax and semantics of extended and normal fuzzy logic programs [30, 23] and disjunctive logic programs [7, 4]. Moreover, we show that extended and normal disjunctive fuzzy logic programs can be intuitively used for representing and reasoning about scheduling with fuzzy preferences.
Inductive logicprogramming (ILP) deals withthe problem of finding a hypothesis covering all positive examples and excluding negative examples. One of the sub-problems is specifying the structure of the hypothesis, t...
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ISBN:
(纸本)9783642154300
Inductive logicprogramming (ILP) deals withthe problem of finding a hypothesis covering all positive examples and excluding negative examples. One of the sub-problems is specifying the structure of the hypothesis, that is, the choice of atoms and position of variables in the atoms. In this paper we suggest using constraint satisfaction to describe which variables are unified in the hypotheses. this corresponds to finding the position of variables in atoms. In particular, we present a constraint model with index variables accompanied by a Boolean model to strengthen inference and hence improve efficiency. the efficiency of models is demonstrated experimentally.
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