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检索条件"任意字段=15th International Conference on Logic for Programming Artificial Intelligence and Reasoning"

共 1554 条记录，以下是391-400 订阅

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Screening a Case Base for Stroke Disease Detection 11th

Screening a Case Base for Stroke Disease Detection

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11th international conference on Hybrid artificial intelligence Systems (HAIS)

作者： Neves, Jose Goncalves, Nuno Oliveira, Ruben Gomes, Sabino Neves, Joao Macedo, Joaquim Abelha, Antonio Analide, Cesar Machado, Jose Santos, Manuel Filipe Vicente, Henrique Univ Minho Ctr Algorithmi Braga Portugal Univ Minho Dept Informat Braga Portugal Drs Nicolas & Asp Dubai U Arab Emirates Univ Evora Escola Ciencias & Tecnol Dept Quim Evora Portugal

ISBN: (纸本)9783319320342;9783319320335

Stroke stands for one of the most frequent causes of death, without distinguishing age or genders. Despite representing an expressive mortality figure, the disease also causes long-term disabilities with a huge recovery time, which goes in parallel with costs. However, stroke and health diseases may also be prevented considering illness evidence. therefore, the present work will start with the development of a decision support system to assess stroke risk, centered on a formal framework based on logic programming for knowledge representation and reasoning, complemented with a Case Based reasoning (CBR) approach to computing. Indeed, and in order to target practically the CBR cycle, a normalization and an optimization phases were introduced, and clustering methods were used, then reducing the search space and enhancing the cases retrieval one. On the other hand, and aiming at an improvement of the CBR theoretical basis, the predicates attributes were normalized to the interval 0...1, and the extensions of the predicates that match the universe of discourse were rewritten, and set not only in terms of an evaluation of its Quality-of-Information (QoI), but also in terms of an assessment of a Degree-of-Confidence (DoC), a measure of one's confidence that they fit into a given interval, taking into account their domains, i.e., each predicate attribute will be given in terms of a pair (QoI, DoC), a simple and elegant way to represent data or knowledge of the type incomplete, self-contradictory, or even unknown.

关键词： Stroke Disease logic programming Knowledge Representation and reasoning Case Based reasoning Similarity Analysis

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Experience-based Learning of Symbolic Numerical Constraints 16

Experience-based Learning of Symbolic Numerical Constraints

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16th IEEE-RAS international conference on Humanoid Robots (Humanoids)

作者： Solak, Gokhan Ak, Abdullah Cihan Sariel, Sanem Istanbul Tech Univ Artificial Intelligence & Robot Lab Comp Engn Dept Istanbul Turkey

ISBN: (纸本)9781509047185

Learning symbolic-level numerical constraints is key to use abstractions in effective reasoning and transfer of knowledge for robot systems. We investigate this problem in an experience-based learning framework which uses inductive logic programming as the learning method. Our particular focus is on learning numerical constraints which is an open issue for ILP systems. Some approaches overcome this by using background knowledge given by domain experts. However, using expert knowledge is both expensive and domain dependent. To obtain more general solutions, numerical constraints should be induced by the robot system itself. For this purpose, we present a constraint induction method based on lazy evaluation, designed for deriving general numerical constraints from observations. We extend Aleph, an existing ILP system based on inverse entailment, with a constraint induction approach using a constraint solver. We analyze our method on some sample scenarios and demonstrate the cases where our method can induce the target concept while the prior lazy evaluation method cannot. Our results indicate that our method can generalize numerical constraints by the self observations of robots.

关键词： experience-based learning inductive logic programming numerical reasoning in robots

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Chest Breadths to Predict Individuals' Age A Case Based View 18

Chest Breadths to Predict Individuals' Age A Case Based View

引用

18th IEEE international conference on Business Informatics (CBI)

作者： Domingues, Andrea Neves, Joao Vicente, Henrique Alves, Victor Neves, Jose Univ Minho Dept Informat P-4719 Braga Portugal Drs Nicolas & Asp Dubai U Arab Emirates Univ Evora Escola Ciencias & Tecnol Dept Quim Evora Portugal Univ Minho Algoritmi Ctr P-4719 Braga Portugal

ISBN: (纸本)9781509032310

It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an artificial intelligence grounded decision support system to predict individual's age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a logic programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. the accuracy of the proposed model is satisfactory, close to 90%.

关键词： Intelligent Systems Chest X-ray Images logic programming Knowledge Representation and Case Based reasoning

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A logical Investigation of Heterogeneous reasoning with Graphs in Elementary Economics 9th

A Logical Investigation of Heterogeneous Reasoning with Grap...

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9th international conference on the theory and Applications of Diagrams (Diagrams)

作者： Takemura, Ryo Nihon Univ Tokyo Japan

ISBN: (纸本)9783319423333;9783319423326

Heterogeneous reasoning is a salient component of logic, mathematics, and computer science. Another remarkable field it applies to is economics. In this paper, we apply the proof-theoretic techniques developed in our previous studies [7,8] to heterogeneous reasoning with graphs in elementary economics. We apply the natural deduction-style formalization, which makes it possible to apply well-developed proof-theoretic techniques to the analysis of heterogeneous reasoning with graphs. We also apply the proof-theoretic analysis of free rides developed in [7], and analyze the efficiency of heterogeneous reasoning with graphs. We further discuss abductive reasoning in elementary economics. Abduction has been discussed by philosophers and logicians, and has been extensively studied in the literature on artificial intelligence (see, for example, [2]). In the context of heterogeneous reasoning, we are able to formalize abductive reasoning in elementary economics in the style we employ in our actual reasoning.

关键词： Economics

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10th international conference on Scalable Uncertainty Management, SUM 2016

10th International Conference on Scalable Uncertainty Manage...

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10th international conference on Scalable Uncertainty Management, SUM 2016

ISBN: (纸本)9783319458557

the proceedings contain 26 papers. the special focus in this conference is on Scalable Uncertainty Management. the topics include: A gentle introduction to reinforcement learning;possibilistic graphical models for uncertainty modeling;on the explanation of same as statements using argumentation;reasoning with multiple-agent possibilistic logic;incremental preference elicitation in multi-attribute domains for choice and ranking with the borda count;graphical models for preference representation;fuzzy labeling for abstract argumentation;a belief-based approach to measuring message acceptability;intertranslatability of labeling-based argumentation semantics;preference inference based on Pareto models;persuasion dialogues via restricted interfaces using probabilistic argumentation;metric logic program explanations for complex separator functions;a two-stage online approach for collaborative multi-agent planning under uncertainty;probabilistic reasoning in the description logic ALCP with the principle of maximum entropy;fuzzy quantified structural queries to fuzzy graph databases;probabilistic spatial reasoning in constraint logic programming;competitive diffusion as a massive multi-player game in social networks;challenges for efficient query evaluation on structured probabilistic data;a measure of referential success based on alpha-cuts and graded justification of arguments via internal and external endogenous features.

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Processing Markov logic Networks with GPUs: Accelerating Network Grounding 1

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25th international conference on Inductive logic programming (ILP)

作者： Alberto Martinez-Angeles, Carlos Dutra, Ines Costa, Vitor Santos Buenabad-Chavez, Jorge CINVESTAV IPN Dept Computac Av Inst Politecn Nacl 2508 Mexico City 07360 DF Mexico CRACS INESC TEC LA Dept Ciencia Comp Rua Campo Alegre 1021 P-4169007 Oporto Portugal Univ Porto Rua Campo Alegre 1021 P-4169007 Oporto Portugal

ISBN: (数字)9783319405667

ISBN: (纸本)9783319405667;9783319405650

Markov logic is an expressive and widely used knowledge representation formalism that combines logic and probabilities, providing a powerful framework for inference and learning tasks. Most Markov logic implementations perform inference by transforming the logic representation into a set of weighted propositional formulae that encode a Markov network, the ground Markov network. Probabilistic inference is then performed over the grounded network. Constructing, simplifying, and evaluating the network are the main steps of the inference phase. As the size of a Markov network can grow rather quickly, Markov logic Network (MLN) inference can become very expensive, motivating a rich vein of research on the optimization of MLN performance. We claim that parallelism can have a large role on this task. Namely, we demonstrate that widely available Graphics Processing Units (GPUs) can be used to improve the performance of a state-of-the-art MLN system, Tuffy, with minimal changes. Indeed, comparing the performance of our GPU-based system, TuGPU, to that of the Alchemy, Tuffy and RockIt systems on three widely used applications shows that TuGPU is up to 15x times faster than the other systems.

关键词： Statistical relational learning Markov logic Markov logic networks Datalog Parallel computing GPUs

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logic & Proofs for Cyber-Physical Systems 8th

Logic & Proofs for Cyber-Physical Systems

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8th international Joint conference on Automated reasoning (IJCAR)

作者： Platzer, Andre Carnegie Mellon Univ Dept Comp Sci Pittsburgh PA 15213 USA

ISBN: (纸本)9783319402291

Cyber-physical systems (CPS) combine cyber aspects such as communication and computer control with physical aspects such as movement in space, which arise frequently in many safety-critical application domains, including aviation, automotive, railway, and robotics. But how can we ensure that these systems are guaranteed to meet their design goals, e.g., that an aircraft will not crash into another one? this paper highlights some of the most fascinating aspects of cyberphysical systems and their dynamical systems models, such as hybrid systems that combine discrete transitions and continuous evolution along differential equations. Because of the impact that they can have on the real world, CPSs deserve proof as safety evidence. Multi-dynamical systems understand complex systems as a combination of multiple elementary dynamical aspects, which makes them natural mathematical models for CPS, since they tame their complexity by compositionality. the family of differential dynamic logics achieves this compositionality by providing compositional logics, programming languages, and reasoning principles for CPS. Differential dynamic logics, as implemented in the theorem prover KeYmaera X, have been instrumental in verifying many applications, including the Airborne Collision Avoidance System ACAS X, the European Train Control System ETCS, automotive systems, mobile robot navigation, and a surgical robot system for skull-base surgery. this combination of strong theoretical foundations with practical theorem proving challenges and relevant applications makes logic for CPS an ideal area for compelling and rewarding research.

关键词： Dynamics

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Question answering via integer programming over semi-structured knowledge 25

Question answering via integer programming over semi-structu...

引用

25th international Joint conference on artificial intelligence, IJCAI 2016

作者： Khashabi, Daniel Khot, Tushar Sabharwal, Ashish Clark, Peter Etzioni, Oren Roth, Dan University of Illinois at Urbana-Champaign IL United States SeattleWA United States

Answering science questions posed in natural language is an important AI challenge. Answering such questions often requires non-trivial inference and knowledge that goes beyond factoid retrieval. Yet, most systems for this task are based on relatively shallow Information Retrieval (IR) and statistical correlation techniques operating on large unstructured corpora. We propose a structured inference system for this task, formulated as an Integer Linear Program (ILP), that answers natural language questions using a semi-structured knowledge base derived from text, including questions requiring multi-step inference and a combination of multiple facts. On a dataset of real, unseen science questions, our system significantly outperforms (+14%) the best previous attempt at structured reasoning for this task, which used Markov logic Networks (MLNs). It also improves upon a previous ILP formulation by 17.7%. When combined with unstructured inference methods, the ILP system significantly boosts overall performance (+10%). Finally, we show our approach is substantially more robust to a simple answer perturbation compared to statistical correlation methods.

关键词： Integer programming

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On Model Finding with Constraint Patterns

On Model Finding with Constraint Patterns

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15th international conference on New Trends in Intelligent Software Methodology Tools, and Techniques (SoMeT)

作者： Duc-Hanh Dang Anh-Hoang Truong Van Hung Dang VNU Univ Engn & Technol Dept Software Engn 144 Xuan Thuy Hanoi Vietnam

ISBN: (纸本)9781614996743;9781614996736

Class models are often employed to represent domains. In order for class models to conform to their intended domain semantics, we need to ensure their precision and consistency. Precision can be achieved by augmenting the models with constraints, and consistency can be achieved by avoiding contradictory constraints. Model finding is a technique to maintain this kind of consistency. It automatically checks the satisfiability of models by using example instances. However, this technique is often inefficient when applied to large models due to the huge search space. In this paper, we propose a technique to narrow the search space by using patterns to represent constraints. Constraint patterns allow us to put further restrictions on the search space. Our case study illustrates that using constraint patterns in this way can improve the verification process.

关键词： OCL Patterns Model Finding Constraint logic programming

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13th international Symposium on Functional and logic programming, FLOPS 2016

13th International Symposium on Functional and Logic Program...

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13th international Symposium on Functional and logic programming, FLOPS 2016

ISBN: (纸本)9783319296036

the proceedings contain 15 papers. the special focus in this conference is on Functional and logic programming. the topics include: the hard-won lessons of the fifth generation computer project;from sets to bits in coq;from proposition to program;the boolean constraint solver of SWI-prolog;probabilistic inference by program transformation in Hakaru;space-efficient planar acyclicity constraints;executable relational specifications of polymorphic type systems using prolog;proof relevant corecursive resolution;a coq library for internal verification of running-times;a transformational approach to parametric accumulated-cost static profiling;polymorphic types in erlang function specifications;declarative foreign function binding through generic programming;incremental computing with abstract data structures and declarative programming with algebra.

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