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检索条件"任意字段=13th International Conference on Inductive Logic Programming"

共 344 条记录，以下是131-140 订阅

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Model Based Task programming for Secure Multimodal Human-Robot Interaction 13

Model Based Task Programming for Secure Multimodal Human-Rob...

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13th international conference on Control Automation Robotics & Vision (ICARCV)

作者： Lin, Liyong Su, Rong Tju, Hendra Suratno Lee, Gerald Seet Gim Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore Singapore

ISBN: (纸本)9781479951994

this note presents a preliminary study on a high-level model based task programming framework for secure multimodal human-robot interaction in industrial context. the case study of robotic polishing tasks, in particular the task of polishing the whole surfaces of objects of interest, is considered. Our main focus is on system modeling and optimal synthesis of surface coverage trajectories in robotic polishing tasks. Two heuristics are proposed to solve the optimal synthesis problem approximately, based on different considerations and assumptions. We then briefly discuss about polishing tasks other than coverage problem that are specifiable in the language of linear temporal logic and state space reduction heuristics based on learning from expert operators. Finally, we introduce a design of the specification input device for the task specification module.

关键词： Human robot interaction

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On automatic theorem proving with ML 13

On automatic theorem proving with ML

引用

13th Mexican international conference on Artificial Intelligence, MICAI 2014

作者： Toriz, Juan Pablo Muñoz Ruiz, Ivan Martínez Ramírez, José Arrazola Facultad de Ciencias Físico Matemáticas Benémerita Universidad Autónoma de Puebla Puebla Mexico

ISBN: (纸本)9781479999002

In this paper, we describe the development of a series of automatic theorem provers for a variety of logics. Provers are developed from a functional approach. the first prover is for Classical Propositional Calculus (CPC), which is based on a constructive proof of Kalmar's theorem. We also provide the implementation of a cut and contraction free sequent calculus for Intuitionistic Propositional logic (IPC). Next, it is introduced a prover for ALCS4, which is the description logic ALC with transitive and reflexive roles only. this prover is also based on a cut and contraction free sequent calculus. We also provide a complexity analysis for each prover. © 2014 IEEE.

关键词： Functional programming

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Fuzzy Sensor-Based Navigation with Neural Tracking Control of the Wheeled Mobile Robot

Fuzzy Sensor-Based Navigation with Neural Tracking Control o...

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13th international conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Szuster, Marcin Hendzel, Zenon Burghardt, Andrzej Rzeszow Univ Technol Dept Appl Mech & Robot PL-35959 Rzeszow Poland

ISBN: (纸本)9783319071756;9783319071763

Navigation of the wheeled mobile robot in the unknown environment with simultaneous realisation of the generated trajectory, is one of the most challenging and up to date problems in the modern mobile robotics. In the article a new approach is presented to a collision-free trajectory generating for a wheeled mobile robot, realised in a form of the hierarchical control system with two layers. the first layer is a tracking control system, where the Neuro-Dynamic programming algorithm in the Dual Heuristic Dynamic programming configuration was applied. the second layer is a trajectory generator where the Fuzzy logic systems were used. the presented control system generates and realises trajectory of the wheeled mobile robot within the complex task of goal-seeking and obstacle avoiding. the proposed hierarchical control system works on-line, its performance was verified using the wheeled mobile robot Pioneer 2-DX.

关键词： Neuro-Dynamic programming Fuzzy System Mobile Robot Neural Networks Path Planning Sensor-Based Navigation

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Modeling natural language metaphors with an answer set programming framework

Modeling natural language metaphors with an answer set progr...

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13th Mexican international conference on Artificial Intelligence, MICAI 2014

作者： Acosta-Guadarrama, Juan Carlos Dávila-Pérez, Rogelio Osorio, Mauricio Zaldivar, Victor Hugo Universidad Autónoma del Estado de México TolucaEstado de México Mexico División de Posgrado Universidad Autónoma de Guadalajara ZapopanJal Mexico Universidad de las Américas. Puebla CholulaPuebla Mexico Departamento de Electrónica Sistemas e Informática Instituto Tecnológico y de Estudios Superiores de Occidente TlaquepaqueJal Mexico

ISBN: (纸本)9783319136462

Metaphors are natural language constructions that play an important role in the way human beings communicate knowledge and understand the world. Some formal philosophers such as Searle and Lakoff claim that the semantic analysis of expressions that involve fictional stories and metaphors are examples of the inadequacy of using predicate logic for the analysis of the meaning of language. D’Hanis proposes that using predicate logic in combination of non-monotonic reasoning is possible to interpret metaphorical expressions. In this paper, we introduce an approach for modelling metaphorical thinking using a particular form of logic programming called answer set programming (ASP). ASP essentially enhances the logical apparatus of predicate calculus by introducing mechanisms such as negation as a failure that enable the system to accomplish non-monotonic reasoning. We show that using ASP is possible to model the meaning of some expressions involving metaphorical constructions and the implementation of metaphorical reasoning mechanisms that could be a great addition to any knowledge-based application. © Springer international Publishing Switzerland 2014.

关键词： logic programming

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A Novel Bayesian Network based Scheme for Finding the Optimal Solution to Stochastic Online Equi-Partitioning Problems 13

A Novel Bayesian Network based Scheme for Finding the <i>Opt...

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13th international conference on Machine Learning and Applications (ICMLA)

作者： Glimsdal, Sondre Granmo, Ole-Christoffer Univ Agder Dept ICT Grimstad Norway

ISBN: (纸本)9781479974153

A number of intriguing decision scenarios, such as order picking, revolve around partitioning a collection of objects so as to optimize some application specific objective function. In its general form, this problem is referred to as the Object Partitioning Problem (OOP), known to be NP-hard. We here consider a variant of OPP, namely the Stochastic Online Equi-Partitioning Problem (SO-EPP). In SO-EPP, objects arrive sequentially, in pairs. the relationship between the arriving object pairs is stochastic: they belong to the same partition with probability p. From a history of object arrivals, the goal is to predict which objects will appear together in future arrivals. As an additional complication, the partitions of related objects are required to be of equal cardinality. the decision maker, however, is not informed about the true relation between the objects, he is merely observing the stream of object pairs, and has to predict future behavior. Inferring the correct partitioning from historical behavior is thus a significant challenge, which becomes even more difficult when p is unknown. Previously, only heuristic sub-optimal solution strategies have been proposed for SO-EPP. In this paper, we propose the first optimal solution strategy. In brief, the scheme that we propose, BN-EPP, is founded on a Bayesian Network representation of SO-EPP problems. Based on probabilistic reasoning we are not only able to infer the correct object partitioning with optimal accuracy. We are also able to simultaneously infer p, allowing us to accelerate learning as object pairs arrive. Being optimal, BN-EPP provides superior performance compared to existing state-of-the-art solution schemes. BN-EPP is also highly flexible, being capable of encoding object partitioning constraints. Finally, BN-EPP is parameter free - its performance does not rely on fine tuning any parameters. As a result of these advantages, BN-EPP opens up for significantly improved performance for OOP based applicat

关键词： belief networks inference mechanisms optimisation BN-EPP Bayesian network representation NP-hard problem OOP SO-EPP novel Bayesian network based scheme object partitioning problem probabilistic reasoning stochastic online equi-partitioning problems Bayes methods Convergence Meteorology Noise Partitioning algorithms Probabilistic logic Stochastic processes Bayesian networks object oriented programming Soft computing Nondeterministic polynomial-time hard Partitioning algorithms Probabilistic logic Inference mechanisms Bayes methods Markov chain Meteorology Converge Noise

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ASP-DPOP: Solving Distributed Constraint Optimization Problems with logic programming 14

ASP-DPOP: Solving Distributed Constraint Optimization Proble...

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international conference on Autonomous Agents and Multiagent Systems

作者： Tiep Le Tran Cao Son Enrico Pontelli William Yeoh Department of Computer Science New Mexico State University

ISBN: (纸本)9781634391313

Researchers have used Distributed Constraint Optimization Problems (DCOPs) to model various multi-agent coordination and resource allocation problems. However, existing DCOP algorithms have focused almost exclusively on imperative programming techniques. this paper explores a new direction, which is to develop algorithms that use declarative programming, specifically logic programming, techniques.

关键词： DCOP ASP Constrained optimization logic programming algorithms Resource utilization Distribute Declarative programming programming TECHNIQUES

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Game theory semantics for PCTL model checking label-extended probabilistic Petri net

Game theory semantics for PCTL model checking label-extended...

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international conference on Computer and Information Science (ACIS)

作者： Yang Liu School of Information Science and Technology Taishan University Taian Shandong China State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu China

Game theory has emerged as the powerful semantics for some programming languages and logical systems. At present, it is even used to model checking-based verification process. PCTL (probabilistic computation tree logic) is the extension of CTL (computation tree logic), which can be used for model checking stochastic system models (i.e., stochastic model checking). Using the label-extended PPN (probabilistic Petri net) system as the high-level model for stochastic system, a game theory-based formal semantics for PCTL model checking is presented, which is intuitive and succinct compared with the classical semantics for PCTL model checking. the game process for PCTL model checking is implemented in the visual prototype tool, and the feasibility is demonstrated by an illustrative example.

关键词： Games Model checking Game theory Semantics Computational modeling Probabilistic logic Stochastic processes

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Model based task programming for secure multimodal human-robot interaction

Model based task programming for secure multimodal human-rob...

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international conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Liyong Lin Rong Su Hendra Suratno Tju Gerald Seet Gim Lee School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781479952007

关键词： Trajectory Optimization Solid modeling Force Robot kinematics programming

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On Automatic theorem Proving with ML

On Automatic Theorem Proving with ML

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Mexican international conference on Artificial Intelligence, MICAI

作者： Juan Pablo Muñoz Toriz Iván Martínez Ruiz José Arrazola Ramírez Fac. de Cienc. Fisico Mat. Benemerita Universidad Autonoma de Puebla Puebla Puebla MX Facultad de Ciencias Físico Matemáticas Benémerita Universidad Autónoma de Puebla Puebla México

关键词： Calculus Bismuth Complexity theory Functional programming Binary trees Artificial intelligence Algorithm design and analysis

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A Statistical Model Checker for Situation Calculus Based Multi-Agent Models 14

A Statistical Model Checker for Situation Calculus Based Mul...

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international conference on Autonomous Agents and Multiagent Systems

作者： Christian Kroiss Institute for Informatics Ludwig-Maximilians-Universitat Munchen

ISBN: (纸本)9781634391313

In this paper we introduce a new approach for multi-agent simulation and statistical model checking that combines the well-established situation calculus with a first order version of bounded linear time logic (BLTL). this creates a fully integrated solution for specifying system behavior and requirements within the same logical framework. We realized the approach in an extensible tool that combines the benefits of constraint logic programming with the versatility of Python and its ecosystem. First experiments show that the approach is applicable to a wide range of problems and that altogether a more flexible modeling-verification workflow is achieved than in most existing solutions.

关键词： Statistical Model Checking Agent-Based Simulation Multi-Agent Systems Situation Calculus Multi-agent systems statistical models (nuclear) Model checking Calculus Calculi checker logic programming Event driven simulation system behavior Pythonidae

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