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检索条件"任意字段=16th International Conference on Inductive Logic Programming"

共 318 条记录，以下是11-20 订阅

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16th international Symposium on Functional and logic programming, FLOPS 2022

16th International Symposium on Functional and Logic Program...

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16th international Symposium on Functional and logic programming, FLOPS 2022

ISBN: (纸本)9783030994600

the proceedings contain 15 papers. the special focus in this conference is on Functional and logic programming. the topics include: Explanations as Programs in Probabilistic logic programming;FOLD-R++: A Scalable Toolset for Automated inductive Learning of Default theories from Mixed Data;a Lazy Desugaring System for Evaluating Programs with Sugars;on Transforming Cut- and Quantifier-Free Cyclic Proofs into Rewriting-Induction Proofs;improving Type Error Reporting for Type Classes;asynchronous Unfold/Fold Transformation for Fixpoint logic;Program logic for Higher-Order Probabilistic Programs in Isabelle/HOL;generating C: System Description;translation Certification for Smart Contracts;zipping Strategies and Attribute Grammars;unified Program Generation and Verification: A Case Study on Number-theoretic Transform;scheduling Complexity of Interleaving Search;preface.

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Efficient Resource-Aware Neural Architecture Search with a Neuro-Symbolic Approach 16

Efficient Resource-Aware Neural Architecture Search with a N...

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16th IEEE international Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)

作者： Bellodi, Elena Bertozzi, Davide Bizzarri, Alice Favalli, Michele Fraccaroli, Michele Zese, Riccardo Univ Ferrara Dept Engn Ferrara Italy Univ Manchester Comp Sci Dept Manchester Lancs England Unitec SpA Lugo Italy Univ Ferrara DOCPAS Ferrara Italy

ISBN: (纸本)9798350393613

Hardware-aware Neural Architectural Search (NAS) is gaining momentum to enable the deployment of deep learning on edge devices with limited computing capabilities. Incorporating device-related objectives such as affordable floating point operations, latency, power, memory usage, etc. into the optimization process makes searching for the most efficient neural architecture more complicated, since both model accuracy and hardware cost should guide the search. the main concern with most state-of-the-art hardware-aware NAS strategies is that they propose for evaluation also trivially infeasible network models for the capabilities of the hardware platform at hand. Moreover, previously generated models are frequently not exploited to intelligently generate new ones, leading to prohibitive computational costs for practical relevance. this paper aims to boost the computational efficiency of hardware-aware NAS by means of a neuro-symbolic framework revolving around a Probabilistic inductive logic programming module to define and exploit a set of symbolic rules. this component learns and refines the probabilities associated with the rules, allowing the framework to adapt and improve over time, thus quickly narrowing down the search space toward the most promising neural architectures.

关键词： architecture search neural network hardware accelerators neural networks probabilistic logic programming

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Applications of Fuzzy Set Models in Optimizing Agricultural Production Structures in Smart Farms 1

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23rd international conference on Next Generation Wired/Wireless Networks and Systems (NEW2AN) / 16th conference on Internet of things and Smart Spaces (RuSMART)

作者： Ishnazarov, Akram Mamasoliyev, Sarvar Tashkent State Univ Econ Dept Math Methods Econ Tashkent Uzbekistan

ISBN: (数字)9783031609978

ISBN: (纸本)9783031609961;9783031609978

this article emphasizes the application of fuzzy logic in the field of agriculture. the use of fuzzy logic is not restricted to specific agricultural domains, but rather extends from soil analysis to the entire process of plant production, encompassing various areas within agriculture. To gain a better understanding of fuzzy logic in agriculture, a concise and comprehensive literature review has been conducted. Crop yield estimation fuzzy logic involves the incorporation of input parameters such as productivity, area, and labor expenses. through the application of fuzzy arithmetic to these parameters, a precise crop yield value is obtained. the fuzzy modeling employs optimal membership functions. the accuracy of the results is verified by comparing them with existing open-source literature.

关键词： fuzzy logic fuzzy inference system membership functions fuzzy mathematical programming problems graded membership

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Automated Generation of Control Concepts Annotation Rules Using inductive logic programming System Description 1

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16th international Symposium on Functional and logic programming (FLOPS)

作者： Shbita, Basel Moitra, Abha Univ Southern Calif Los Angeles CA 90007 USA Gen Elect Res Niskayuna NY 12309 USA GE Global Res Niskayuna NY USA

ISBN: (数字)9783030994617

ISBN: (纸本)9783030994600;9783030994617

Capturing domain knowledge is a time-consuming procedure that usually requires the collaboration of a Subject Matter Expert (SME) and a modeling expert to encode the knowledge. this situation is further exacerbated in some domains and applications. the SME may find it challenging to articulate the domain knowledge as a procedure or a set of rules but may find it easier to classify instance data. In the cyber-physical domain, inferring the implemented mathematical concepts in the source code or a different form of representation, such as the Resource Description Framework (RDF), is difficult for the SME, requiring particular expertise in low-level programming or knowledge in Semantic Web technologies. To facilitate this knowledge elicitation from SMEs, we developed a system that automatically generates classification and annotation rules for control concepts in cyber-physical systems (CPS). Our proposed approach leverages the RDF representation of CPS source code and generates the rules using inductive logic programming and semantic technologies. the resulting rules require a small set of labeled instance data that is provided interactively by the SME through a user interface within our system. the generated rules can be inspected, iterated and manually refined.

关键词： Knowledge capture Semantic model Knowledge graphs Rules Rule annotation Cyber-physical systems

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On Transforming Cut- and Quantifier-Free Cyclic Proofs into Rewriting-Induction Proofs 1

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16th international Symposium on Functional and logic programming (FLOPS)

作者： Zhang, Shujun Nishida, Naoki Nagoya Univ Grad Sch Informat Nagoya 4648601 Japan

ISBN: (数字)9783030994617

ISBN: (纸本)9783030994600;9783030994617

An inductive definition set (IDS, for short) of first-order predicate logic can be transformed into a many-sorted term rewrite system (TRS, for short) such that a quantifier-free sequent is valid w.r.t. the IDS if and only if a term equation representing the sequent is an inductive theorem of the TRS. In this paper, to compare rewriting induction (RI, for short) with cyclic proof systems, under certain assumptions, we show that if a sequent has a cut- and quantifier-free cyclic proof, then there exists an RI proof for a term equation of the sequent. To this end, we propose a transformation of a cut- and quantifier-free cyclic proof of the sequent into an RI proof for the corresponding equation.

关键词： Term rewriting Rewriting induction Cyclic proof inductive theorem proving Sequent calculus

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16th international Symposium on NASA Formal Methods, NFM 2024

16th International Symposium on NASA Formal Methods, NFM 202...

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16th international Symposium on NASA Formal Methods, NFM 2024

ISBN: (纸本)9783031606977

the proceedings contain 26 papers. the special focus in this conference is on NASA Formal Methods. the topics include: Formalization of Asymptotic Convergence for Stationary Iterative Methods;distributional Probabilistic Model Checking;quantitative Input Usage Static Analysis;Verifying a C Implementation of Derecho’s Coordination Mechanism Using VST and Coq;verification of Scapegoat Trees Using Dafny;Real Arithmetic in TLAPM;deductive Model Refinement;symmetry-Based Abstraction Algorithm for Accelerating Symbolic Control Synthesis;SMT-Based Aircraft Conflict Detection and Resolution;towards Formal Verification of Neural Networks in Cyber-Physical Systems;approximate Conformance Verification of Deep Neural Networks;compositional inductive Invariant Based Verification of Neural Network Controlled Systems;tree-Based Scenario Classification;validation of Reinforcement Learning Agents and Safety Shields with ProB;contract-Driven Runtime Adaptation;topllet: An Optimized Engine for Answering Metric Temporal Conjunctive Queries;a Formal Verification Framework for Runtime Assurance;SMT-Based Dynamic Multi-Robot Task Allocation;control Barrier Function Toolbox: An Extensible Framework for Provable Safety;Robotics: A New Mission for FRET Requirements;safe Planning through Incremental Decomposition of Signal Temporal logic Specifications;structuring Formal Methods into the Undergraduate Computer Science Curriculum;integrated Contract-Based Unit and System Testing for Component-Based Systems;Verifying PLC Programs via Monitors: Extending the Integration of FRET and PLCverif.

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An Integrated Development Environment for the Design of Fuzzy Human-centric System in Accordance with IEEE Standard 1855-2016 23

An Integrated Development Environment for the Design of Fuzz...

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16th ACM international conference on Pervasive Technologies Related to Assistive Environments (PETRA)

作者： Pandya, Bhavesh Pourabdollah, Amir Lotfi, Ahmad Nottingham Trent Univ Sch Sci & Technol Nottingham England

ISBN: (纸本)9798400700699

A fuzzy logic System (FLS) has the unique potential of intelligent decision-making capability with the input data, which are imprecise and unpredictable but can be expressed using linguistic rules. However, such FLS strongly depends on the hardware architecture of the systems under consideration. A language called Fuzzy Markup Language (FML), which is based on XML, has the ability to express fuzzy systems without taking into account either hardware or software restrictions, thus enabling sharing effectively among distributed environments. FML creates a unified and clearly defined FLS that is independent of its previous representation. It also increases the capabilities of system designers by giving them access to a range of services that accelerate the process of creating a distributed or centralised fuzzy system. this can be done either through a centralised cloud-based platform or through a distributed cloud-based platform. FML-related software libraries, such as Simpful (a Python-based library) and Java FML (JFML, a Java-based library), have added to the novelty in it. However, JFML and Simpful enable fuzzy system modeling for programmers only in the abovementioned programming languages. Hence a need for the development of an open-source FLS which will be capable of enabling fuzzy system-based modelling is felt. the present communication introduces an enhancement of JFML through a visual environment based on GUI following IEEE Std 1855-2016. the functionalities of user-friendly visual FML are developed considering the data related to Human Activity Recognition (HAR) and other physiological data like SpO(2) and pulse rate obtained from wearable sensors to compare the performances.

关键词： gui fml fls fuzzy logic azure real-time soa jfml

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INDUSTRIAL MODELING AND programming LANGUAGE (IMPL) FOR COMPLEX DATA ANALYTICS AND DECISION-MAKING PROBLEMS 16

INDUSTRIAL MODELING AND PROGRAMMING LANGUAGE (IMPL) FOR COMP...

引用

16th international conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected Smart Cities, CSC 2022, 7th international conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th international conference on theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi conference on Computer Science and Information Systems, MCCSIS 2022

作者： Menezes, Brenno Kelly, Jeffrey Elsherif, Munier Franzoi, Robert Division of Engineering Management College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Education City LAS Building Doha Qatar Industrial Algorithms Limited. Toronto Canada Department of Chemical Engineering Faculty of Engineering University of Tripoli Tripoli Libya

ISBN: (纸本)9789898704429

the Industrial Modeling and programming Language (IMPL) is a sophisticated computational system for tackling large-scale and complex-scope data analytics and decision-making problems in the engineering and operations research fields. Although the software provides both scalar-based (e.g., MATLAB) and set-based modeling (GAMS, AIMMS, AMPL, MOSEL, OPL) as found in most of the modeling programming languages (MPL), IMPL is mainly built as ad hoc and specialized proprietary industrial software platform (closed-source). this is made by built-in structured- and semantic-based modeling that rely on the Unit-Operation-Port-State Superstructure (UOPSS) constructs (for the structure) and Quantity-logic-Quality Phenomena (QLQP) concepts (for the semantics). Besides the data analytics package included in the IMPL-DATA version, this mathematical programming language enables the modeling and solving of industrial-scale discrete, nonlinear, and dynamic optimization, estimation, and simulation problems found in both the batch and continuous process industries. IMPL's data analytics (DA) includes several functions to concatenate, substitute, sort, cluster, regress, etc., datasets in order to categorize, reduce, track, etc., the given data. IMPL's decision-making (DM) is suitable to support the modeling and solving of design, planning, scheduling, coordinating production, process, operations, optimization, and control problems as well as parameter identification, estimation, and data reconciliation problems. IMPL includes links to various community and commercial LP, QP, MILP and NLP solvers. To summarize, IMPL may be considered as a confluence with the scientific disciplines of applied engineering, management, information and computer science, statistical and data science. © MCCSIS *** rights reserved.

关键词： Semantics

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Learning and Revising Dynamic Temporal theories in the Full Discrete Event Calculus 1

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30th international conference on inductive logic programming (ILP) held as part of the 1st international Joint conference on Learning and Reasoning (IJCLR)

作者： Ray, Oliver Univ Bristol Dept Comp Sci Bristol Avon England

ISBN: (数字)9783030974541

ISBN: (纸本)9783030974541;9783030974534

this paper presents the first automatic method for learning and revising dynamic temporal theories in the full-fledged Discrete Event Calculus (DEC), where fluents may be temporarily released from the law of inertia and subject to qualitative or quantitative domain laws. this is done by proposing a reformulation of the DEC, called the eXploratory Event Calculus (XEC), which can be more efficiently handled by state-of-the-art answer set solvers, and which supports a range of different logical semantics and policy options for resolving conflicts relating to the truth value or release status of fluents. the paper shows how XEC outperforms DEC on standard reasoning benchmarks, and how it can be used with an ILP system XHAIL to provide the first proof-of-principle demonstration of theory learning and revision in the full-featured DEC.

关键词： theory revision Answer set programming Event calculus

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Learning to Rank the Distinctiveness of Behaviour in Serial Offending 16th

Learning to Rank the Distinctiveness of Behaviour in Serial ...

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16th international conference on logic programming and Non-Monotonic Reasoning (LPNMR)

作者： Law, Mark Sautory, theophile Mitchener, Ludovico Davies, Kari Tonkin, Matthew Woodhams, Jessica Alrajeh, Dalal ILASP Ltd Grantham England Univ Calif Berkeley Berkeley CA 94720 USA Imperial Coll London London England Univ Bournemouth Bournemouth Dorset England Univ Leicester Leicester Leics England Univ Birmingham Birmingham W Midlands England

ISBN: (纸本)9783031157073;9783031157066

Comparative Case Analysis is an analytical process used to detect serial offending. It focuses on identifying distinctive behaviour that an offender displays consistently when committing their crimes. In practice, crime analysts consider the context in which each behaviour occurs to determine its distinctiveness, which subsequently impacts on their determination of whether crimes are committed by the same person or not. Existing algorithms do not currently consider context in this way when generating linkage predictions. this paper presents the first learning-based approach aimed at identifying contexts within which behaviour may be considered more distinctive. We show how this problem can be modelled as that of learning preferences (in answer set programming) from examples of ordered pairs of contexts in which a behaviour was observed. In this setting, a context is preferred to another context if the behaviour is rarer in the first context. We make novel use of odds ratios to determine which examples are used for learning. Our approach has been applied to a real dataset of serious sexual offences provided by the UK National Crime Agency. the approach provides (i) a systematic methodology for selecting examples from which to learn preferences;(ii) novel insights for practitioners into the contexts under which an exhibited behaviour is more rare.

关键词： Crime Linkage Answer Set programming inductive logic programming

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