the proceedings contain 25 papers. the special focus in this conference is on inductivelogicprogramming. the topics include: A personal view of how best to apply ILP;agents that reason and learn;mining model trees;c...
ISBN:
(纸本)9783540399179
the proceedings contain 25 papers. the special focus in this conference is on inductivelogicprogramming. the topics include: A personal view of how best to apply ILP;agents that reason and learn;mining model trees;complexity parameters for first-order classes;a multi-relational decision tree learning algorithm;applying theory revision to the design of distributed databases;disjunctive learning with a soft-clustering method;ILP for mathematical discovery;an exhaustive matching procedure for the improvement of learning efficiency;efficient data structures for inductivelogicprogramming;graph kernels and gaussian processes for relational reinforcement learning;on condensation of a clause;a comparative evaluation of feature set evolution strategies for multi-relational boosting;comparative evaluation of approaches to propositionalization;improved distances for structured data;induction of enzyme classes from biological databases;estimating maximum likelihood parameters for stochastic context-free graph grammars;induction of the effects of actions by monotonic methods;hybrid abductive inductive learning;query optimization in inductivelogicprogramming by reordering literals;efficient learning of unlabeled term trees with contractible variables from positive data;relational IBL in music with a new structural similarity measure and an effective grammar-based compression algorithm for tree structured data.
the proceedings contain 24 papers from the inductivelogicprogramming - 13thinternationalconference, ILP 2003. the topics discussed include: complexity parameters for first-order classes;applying theory revision to...
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the proceedings contain 24 papers from the inductivelogicprogramming - 13thinternationalconference, ILP 2003. the topics discussed include: complexity parameters for first-order classes;applying theory revision to the design of distributed databases;ILP for mathematical discovery;efficient data structures for inductivelogicprogramming;graph kernels and gaussian processes for relational reinforcement learning and on condensation of a clause.
this volume contains the refereed proceedings of the 13thinternationalconference on logicprogramming and Nonmonotonic Reasoning, LPNMR 2015, held in September 2015 in Lexington, KY, USA. the 290long and 11 short pa...
ISBN:
(数字)9783319232645
ISBN:
(纸本)9783319232638;9783319232645
this volume contains the refereed proceedings of the 13thinternationalconference on logicprogramming and Nonmonotonic Reasoning, LPNMR 2015, held in September 2015 in Lexington, KY, USA. the 290long and 11 short papers presented together with 3 invited talks, the paper reporting on the Answer Set programming competition, and four papers presented by LPNMR student attendees at the doctoral consortium were carefully reviewed and selected from 60 submissions. LPNMR is a forum for exchanging ideas on declarative logicprogramming, nonmonotonic reasoning, and knowledge representation. the aim of the LPNMR conferences is to facilitate interactions between researchers interested in the design and implementation of logic-based programming languages and database systems, and researchers who work in the areas of knowledge representation and nonmonotonic reasoning.
the proceedings contain 38 papers. the topics discussed include: deciding satisfiability of positive second order joinability formulae;SAT solving for argument filterings;inductive decidability using implicit inductio...
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ISBN:
(纸本)3540482814
the proceedings contain 38 papers. the topics discussed include: deciding satisfiability of positive second order joinability formulae;SAT solving for argument filterings;inductive decidability using implicit induction;matching modulo superdevelopments applications to second-order matching;a characterization of alternating log time by first order functional programs;combining typing and size constraints for checking the termination of higher-order conditional rewrite systems;on a local-step cut-elimination procedures for the intuitionistic sequent calculus;branching-time temporal logic extended with qualitative Presburger constraints;combining supervaluation and degree based reasoning under vagueness;a local system for intuitionistic logic;reducing nondeterminism in the calculus of structures;a relaxed approach to integrity and inconsistency in databases;on locally checkable properties;and deciding key cycles for security protocols.
the proceedings contain 8 papers. the topics discussed include: term indexing for the LEO-II Prover;integrating external deduction tools with ACL2;efficiently checking propositional resolution proofs in Isabelle/HOL;t...
the proceedings contain 8 papers. the topics discussed include: term indexing for the LEO-II Prover;integrating external deduction tools with ACL2;efficiently checking propositional resolution proofs in Isabelle/HOL;tableau decision procedure for propositional intuitionistic logic;LIFT-UP: lifted first-order planning under uncertainty;multiple preprocessing for systematic SAT solvers;implementing an instantiation-based theorem prover for first-order logic;and algorithms and data structures for first-order equational deduction.
the proceedings contain 48 papers. the special focus in this conference is on logicprogramming and Nonmonotonic Reasoning. the topics include: Stable models for temporal theories;algorithmic decision theory meets log...
ISBN:
(纸本)9783319232638
the proceedings contain 48 papers. the special focus in this conference is on logicprogramming and Nonmonotonic Reasoning. the topics include: Stable models for temporal theories;algorithmic decision theory meets logic;relational and semantic data mining;shift design with answer set programming;advances in WASP;improving coordinated SMT-based system synthesis by utilizing domain-specific heuristics;integrating ASP into ROS for reasoning in robots;automated inference of rules with exception from past legal cases using ASP;solving constraint satisfaction problems with answer set programming;a theory of intentions for intelligent agents;answer set programming modulo acyclicity;a framework for goal-directed query evaluation with negation;implementing preferences with asprin;diagnosing automatic whitelisting for dynamic remarketing ads using hybrid ASP;performance tuning in answer set programming;enablers and inhibitors in causal justifications of logic programs;efficient problem solving on tree decompositions using binary decision diagrams;knowledge acquisition via non-monotonic reasoning in distributed heterogeneous environments;a formal theory of justifications;a new computational logic approach to reason with conditionals;interactive debugging of non-ground ASP programs;linking open-world knowledge bases using nonmonotonic rules;ASP, amalgamation, and the conceptual blending workflow;diagnostic reasoning for robotics using action languages;connecting object-oriented and logicprogramming;reasoning with forest logic programs using fully enriched automata;ASP solving for expanding universes and combining heuristics for configuration problems using answer set programming;infinitary equilibrium logic and strong equivalence and compacting boolean formulae for inference in probabilistic logicprogramming.
Research on natural language interfaces has mainly concentrated on question interpretation as well as answer computation, but not focused as Much on answer presentation. In most natural language interfaces, answers ar...
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Research on natural language interfaces has mainly concentrated on question interpretation as well as answer computation, but not focused as Much on answer presentation. In most natural language interfaces, answers are in fact provided extensionally as a list of all those instances satisfying the query description. In this paper, we aim to go beyond such a mere listing of facts and move towards producing additional descriptions of the query results referred to as intensional answers. We define an intensional answer (IA) as a logical description of the actual set of answer items to a given query in terms of properties that are shared by exactly these answer items. We argue that IAs can enhance a user's understanding of the answer itself but also of the underlying knowledge base. In particular, we present an approach for computing an intensional answer given an extensional answer (i.e. a set of entities) returned as a result of a question. In our approach, an intensional answer is represented by a clause and computed based on inductivelogicprogramming (ILP) techniques, in particular bottom-up clause generalization. the approach is evaluated in terms of usefulness and time performance, and we discuss its potential for helping to detect flaws in the knowledge base as well as to interactively enrich it with new knowledge. While the approach is used in the context of a natural language question answering system in our settings, it clearly has applications beyond, e.g. in the context of research on generating referring expressions. (C) 2009 Elsevier B.V. All rights reserved.
Query optimization is used frequently in relational database management systems. Most existing techniques axe based on reordering the relational operators, where the most selective operators are executed first. In thi...
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ISBN:
(纸本)3540201440
Query optimization is used frequently in relational database management systems. Most existing techniques axe based on reordering the relational operators, where the most selective operators are executed first. In this work we evaluate a similar approach in the context of inductivelogicprogramming (ILP). there are some important differences between relational database management systems and ILP systems. We describe some of these differences and list the resulting requirements for a reordering transformation suitable for ILP. We propose a transformation that meets these requirements and an algorithm for estimating the computational cost of literals, which is required by the transformation. Our transformation yields a significant improvement in execution time on the Carcinogenesis data set.
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