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3rd international Conference on Category Theory and Computer Science, CTCS 1989

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3rd international Conference on Category Theory and Computer Science, CTCS 1989

ISBN: (纸本)9783540516620

The proceedings contain 21 papers. The special focus in this conference is on Category Theory and Computer Science. The topics include: Preface;coherence and valid isomorphism in closed categories applications of proof theory to category theory in a computer scientist perspective;independence results for calculi of dependent types;quantitative domains, groupoids and linear logic;graded multicategories of polynomial-time realizers;on the semantics of second order lambda calculus: From Bruce-Meyer-Mitchell models to hyperdoctrine models and vice-versa;dictoses;declarative continuations: An investigation of duality in programming language semantics;logic representation in LF: Report on work in progress;unification properties of commutative theories: A categorical treatment;an abstract formulation for rewrite systems;from Petri nets to linear logic;an algebraic view of interleaving and distributed operational semantics for CCS;a dialectica-like model of linear logic;a final coalgebra theorem;temporal structures;compositional relational semantics for indeterminate dataflow networks;operations on records;projections for polymorphic strictness analysis;a category-theoretic account of program modules;a note on categorical datatypes;a set constructor for inductive sets in Martin-Löf's type theory.

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ON THE representation OF DATA IN LAMBDA-CALCULUS 3rd

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3rd workshop ON COMPUTER SCIENCE logic ( CSL 89 )

作者： PARIGOT, M Equipe de Logique CNRS UA 753 Université Paris 7 UFR de Mathématiques 2 place Jussieu PARIS Cedex 05 75251 France

ISBN: (纸本)3540527532

We analyse the algorithmic properties of programs induced by the choice of the representation of data in lambda-calculus. From a logical point of view there are two canonical ways of defining the data types: the iterative one and the recursive one. Both define the same mathematical object, but we show that they have a completely different algorithmic content. The essential of the difference appears in the operational properties of two programs: the predecessor and the addition on the type of unary natural numbers (for the type of lists this would be the programs cdr and append). The results we prove in this paper state a fundamental duality between the iterative and recursive representation of data in lambda-calculus. For the iterative representation of natural numbers (Church numerals) there is a “one-step” addition, but we prove in §3 that there is no “one-step” predecessor (by “one-step” we mean “whose computation requires only number of reduction steps bounded by a constant”). For the recursive representation of natural numbers we have the converse situation: there is a “one-step” predecessor but we prove in §4 that there is no “one-step” addition. For simplicity, we state these results for the type of natural numbers, but they hold in fact for all the usual data types defined as ultisorted term algebras. Their practical significance for programming, may be, appears clearer on the type of lists where the predecessor is replaced by the cdr and the addition by append. In §5, we briefly present a new representation of natural numbers for which we have both, a “one-step” predecessor and a “one-step” addition. © Springer-Verlag Berlin Heidelberg 1990.

关键词： Calculations

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AGENP: An ASGrammar-based GENerative Policy Framework 2nd

AGENP: An ASGrammar-based GENerative Policy Framework

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23rd European Symposium on Research in Computer Security (ESORICS) / 2nd international workshop on Policy-Based Autonomic Data Governance (PADG

作者： Calo, Seraphin Manotas, Irene de Mel, Geeth Cunnington, Daniel Law, Mark Verma, Dinesh Russo, Alessandra Bertino, Elisa IBM TJ Watson Res Ctr Distributed AI Dept Yorktown Hts NY 10549 USA Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA IBM Res UK Hartree Ctr Warrington Cheshire England IBM Res UK Emerging Technol Hursley Pk Hursley England Imperial Coll London South Kensington Campus London England

ISBN: (纸本)9783030172770;9783030172763

Generative policies have been proposed as a mechanism to learn the constraints and preferences of a system-especially complex systems such as the ones found in coalitions-in a given context so that the system can adapt to unexpected changes seamlessly, thus achieving the system goals with minimal human intervention. Generative policies can help a coalition system to be more effective when working in a distributed, continuously transforming environment with a diverse set of members, resources, and tasks. Learning mechanisms based on logic programming, e.g., Inductive logic programming (ILP), have several properties that make them suitable and attractive for the creation and adaptation of generative policies, such as the ability to learn a general model from a small number of examples, and being able to incorporate existing background knowledge. ILP has recently been extended with the introduction of systems for Inductive Learning of Answer Set Programs (ILASP) which are capable of supporting automated acquisition of complex knowledge such as constraints, preferences and rule-based models. Motivated by the capabilities of ILASP, we present AGENP, an Answer Set Grammar-based Generative Policy Framework for Autonomous Managed Systems (AMS) that aims to support the creation and evolution of generative policies by leveraging ILASP. We describe the framework components, i.e., inputs, data structures, mechanisms to support the refinement and instantiation of policies, identification of policy violations, monitoring of policies, and policy adaptation according to changes in the AMS and its context. Additionally, we present the main work-flow for the global and local refinement of policies and their adaptation based on Answer Set programming (ASP) for policy representation and reasoning using ILASP. We then discuss an application of the AGENP framework and present preliminary results.

关键词： Inductive logic programming (ILP)

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STARLET : An affix-based compiler compiler designed as a logic programming system 3rd

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3rd international workshop on Compiler Compilers, CC 1990

作者： Beney, Jean Boulicaut, Jean-François Institut National des Sciences Appliquées de Lyon Laboratolre d’Informatique Appliquée Batiment 502 Villeurbanne CedexF-69621 France Ecole Centrale de Lyon Departement Mathématiques-Informatique-Systèmes BP 163 Ecully CedexF-69131 France

ISBN: (纸本)9783540536697

We present STARLET, a new compiler compiler which compiles Extended Affix Grammars defining a translation into an executable program : the translator. We look at its operational semantics and we focus on the points which are close to or different from Prolog procedural semantics. We discuss the two interwoven issues which are Program Reliability (due to many static checks) and Program Efficiency (optimizations at compile time). Both are reached through a systematic use of grammatical properties. © Springer-Vertag Berlin Heidelberg 1991.

关键词： logic programming

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CONTROLLING TRAINING OF NEURAL NETWORK CLASSIFIERS WITH FUZZY-logic

CONTROLLING TRAINING OF NEURAL NETWORK CLASSIFIERS WITH FUZZ...

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3rd workshop ON NEURAL NETWORKS : ACADEMIC / INDUSTRIAL / NASA / DEFENSE ( WNN 92 )

作者： DEROUIN, E BROWN, J Thought Processes Inc Maitland United States

ISBN: (纸本)1565550072

Neural networks have proven very useful in the field of pattern classification by mapping input patterns into one of several categories. The most popular methods of training neural networks use gradient descent techniques to minimize mean square error measured against a training set. The composition of this training set, therefore, will determine the performance of the resulting trained network. Deficiencies in the training set, such as unequal class representation or ineffective training vectors will diminish the network's ultimate performance. Additionally, the characteristics of the training set will implicitly set network performance goals that may or may not match the desired goals of the network designer. This paper investigates the utilization of a fuzzy system to overcome these training set inadequacies by incorporating performance goals into the training strategy. Fuzzy control is used to modify the learning rate parameter during backpropagation training. The method is tested using artificial training data and real-world hyperspectral imagery.

关键词： Neural networks

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Meta-programming for reordering literals in deductive databases 3rd

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3rd international workshop on Meta-programming in logic, META 1992

作者： Träff, Jesper Larsson Prestwich, Steven David ECRC - European Computer-Industry Research Centre Arabellastrasse 17 Munich 81D-8000 Germany

ISBN: (纸本)9783540562825

Specifying efficient evaluation strategies by meta-interpreters, and then eliminating the interpretation overhead by partial evaluation with respect to given object programs, is an elegant technique for the transformation of logic programs. In this paper we show how to apply this technique to the compilation of instantiation based evaluation strategies for DATALOG with negation, and hence to query optimization in deductive databases. We demonstrate our approach on two well-known optimizations, dealing with the passing of information :between literals (sideways information passing strategies or SIPS), and the early evaluation of constraining literals (the C-transformation). © Springer-Verlag Berlin Heidelberg 1992.

关键词： Intelligent databases

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Probabilistic constraint logic theories 3

Probabilistic constraint logic theories

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3rd international workshop on Probabilistic logic programming, PLP 2016

作者： Alberti, Marco Bellodi, Elena Cota, Giuseppe Lamma, Evelina Riguzzi, Fabrizio Zese, Riccardo Dipartimento di Matematica e Informatica - University of Ferrara Via Saragat 1 FerraraI-44122 Italy Dipartimento di Ingegneria - University of Ferrara Via Saragat 1 FerraraI-44122 Italy

Probabilistic logic models are used ever more often to deal with the uncertain relations typical of the real world. However, these models usually require expensive inference procedures. Very recently the problem of identifying tractable languages has come to the fore. In this paper we consider the models used by the learning from interpretations ILP setting, namely sets of integrity constraints, and propose a probabilistic version of them. A semantics in the style of the distribution semantics is adopted, where each integrity constraint is annotated with a probability. These probabilistic constraint logic models assign a probability of being positive to interpretations. This probability can be computed in a time that is logarithmic in the number of ground instantiations of violated constraints. This formalism can be used as the target language in learning systems and for declaratively specifying the behavior of a system. In the latter case, inference corresponds to computing the probability of compliance of a system's behavior to the model. © 2016, CEUR-WS. All rights reserved.

关键词： Probabilistic logics

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Interoperability between bioinformatics tools: A logic programming approach 1

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3rd international Symposium on Practical Aspects of Declarative Languages, PADL 2001

作者： Iglesias, Juan R Gupta, Gopal Pontelli, Enrico Ranjan, Desh Milligan, Brook Dept Computer Science New Mexico State University United States Dept of Biology New Mexico State University United States Dept of Computer Science DallasUT United States

ISBN: (数字)9783540452416

ISBN: (纸本)9783540417682

The goal of this project is to develop solutions to enhance interoperability between bioinformatics applications. Most existing applications adopt different data formats, forcing biologists into tedious translation work. We propose to use of Nexus as an intermediate representation language. We develop a complete grammar for Nexus and we adopt this grammar to build a parser. The construction heavily relies on the peculiar features of Prolog, to easily derive effective parsing and translating procedures. We also develop a general parse tree format suitable for interconversion between Nexus andot her formats. © Springer-Verlag Berlin Heidelberg 2001

关键词： logic programming

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Learning complex activity preconditions in process mining 3

Learning complex activity preconditions in process mining

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3rd international workshop on New Frontiers in Mining Complex Patterns, NFMCP 2014 held in Conjunction with European Conference on Machine Learning and Principles and Practice of knowledge Discovery in Databases, ECML-PKDD 2014

作者： Ferilli, Stefano De Carolis, Berardina Esposito, Floriana Dipartimento di Informatica Università di Bari Bari Italy Centro Interdipartimentale per la Logica e sue Applicazioni Università di Bari Bari Italy

ISBN: (纸本)9783319178752

The availability of automatic support may sometimes determine the successful accomplishment of a process. Such a support can be provided if a model of the intended process is available. Many real-world process models are very complex. Additionally, their components might be associated to conditions that determine whether they are to be carried out or not. These conditions may be in turn very complex, involving sequential relationships that take into account the past history of the current process execution. In this landscape, writing and setting up manually the process models and conditions might be infeasible, and even standard Machine Learning approaches may be unable to infer them. This paper presents a First-Order logic-based approach to learn complex process models extended with conditions. It combines two powerful Inductive logic programming systems. The overall system was exploited to learn the daily routines of the user of a smart environment, for predicting his needs and comparing the actual situation with the expected one. In addition to proving the efficiency and effectiveness of the system, the outcomes show that complex, human-readable and interesting preconditions can be learned for the tasks involved in the process. © Springer international Publishing Switzerland 2015.

关键词： Inductive logic programming (ILP)

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Advanced Languages of Terms for Ontologies 35

Advanced Languages of Terms for Ontologies

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35th international workshop on Description logics, DL 2022

作者： Balbiani, Philippe Diéguez, Martin Gencer, Çiğdem Institut de recherche en informatique de Toulouse CNRS-INPT-UT3 Université de Toulouse Toulouse France Laboratoire d’étude et de recherche en informatique d’Angers University of Angers Angers France Faculty of Arts and Sciences Istanbul Aydın University Istanbul Turkey

This paper is about the integration in a unique formalism of knowledge representation languages such as those provided by description logic languages and rule-based reasoning paradigms such as those provided by logic programming languages. We aim at creating an hybrid formalism where description logics constructs are used for defining concepts that are given as arguments to the predicates of the logic programs. © 2022 Copyright for this paper by its authors.

关键词： Data description

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