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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Emna Ayari Samah Hadouaj Khaled Ghedira LI3 : Laboratoire Ingénierie Informatique Intelligente High Institute of management Tunis Tunisia

One of the current challenges in the development of robot control systems is making them capable of intelligent and suitable responses to changing environments. But, the control of the robot's behavior in uncertain and dynamic environments is very challenging when the problem is how to guarantee the robot's safety by minimizing the interaction with other actors. The most popular methods are based on reactive local navigation schemes that tightly couple the robot actions to the sensor information. These approaches are well based on distance between the robot and the obstacles. This information does not allow the robot to make an intelligent decision while it navigates in unknown environments. Whereas, the robot needs to anticipate environment evolution in order to minimize interaction and avoid conflict with other agents. In this paper, we present a multi-agent simulation model of an autonomous robot in dynamic and uncertain environments. We focus on cases of interactions between agents sharing the same space. The robot should minimize the conflict with other agents when it navigates headed for its goal. Our model is based on fuzzy logic technique in order to deal with the uncertainty of perception.

关键词： Robot sensing systems Navigation Collision avoidance Fuzzy logic Multiagent systems Angular velocity

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Combining Mixed Integer programming and Supervised Learning for Fast Re-planning

Combining Mixed Integer Programming and Supervised Learning ...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Emmanuel Rachelson Ala Ben Abbes Sebastien Diemer Department of EECS University of Liège Liège Belgium Optimisation EDF R&D Clamart France

We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised Learning method for the offline construction of a predictor which takes the problem's parameters as input and infers values for the discrete optimization variables. This way, the online resolution time of the plan repair problem can be greatly decreased by avoiding a large part of the combinatorial search among discrete variables. This contribution was motivated by the large-scale problem of intra-daily recourse strategy computation in electrical power systems. We report and discuss results on this benchmark, illustrating the different aspects and mechanisms of this new approach which provided close-to-optimal solutions in only a fraction of the computational time necessary for existing solvers.

关键词： Planning Production Training Boosting Electricity Complexity theory Search problems

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Lazy Probability Propagation on Gaussian Bayesian Networks

Lazy Probability Propagation on Gaussian Bayesian Networks

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Hua Mu Meiping Wu Hongxu Ma Tim Bailey The Department of Automatic Control National University of Defense Technology Changsha Hunan China Australian Centre for Field Robotics University of Sydney Sydney NSW Australia

Novel lazy Lauritzen-Spiegelhalter (LS), lazy Hugin and lazy Shafer-Shenoy (SS) algorithms are devised for Gaussian Bayesian networks (BNs). In the lazy algorithms, the clique potentials and separator potentials are kept in combinable decomposed form instead of combined to be a single valuation in conventional junction tree algorithms. By employing decomposed form potentials, the independence relations between variables are explored online and the directed graph information is utilized in the message calculations. In the proposed algorithms, a consistent junction tree with the evidence entered can be obtained by a single round of message passing. The moments form parametrization of Gaussian distributions allows the deterministic relationships between variables. Preliminary analysis shows that the lazy LS algorithm and the lazy Hugin algorithm are more computationally efficient than the lazy SS algorithm, especially when there are multiple items of evidence to be incorporated.

关键词： Junctions Inference algorithms Message passing Silicon Probabilistic logic Algorithm design and analysis Particle separators

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PERFICT: Perturbed Frequent Itemset Based Classification Technique

PERFICT: Perturbed Frequent Itemset Based Classification Tec...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Raghvendra Mall Prakhar Jain Vikram Pudi Indian Institute of Information Technology Hyderabad India

This paper presents Perturbed Frequent Itemset based Classification Technique (PERFICT), a novel associative classification approach based on perturbed frequent itemsets. Most of the existing associative classifiers work well on transactional data where each record contains a set of boolean items. They are not very effective in general for relational data that typically contains real valued attributes. In PERFICT, we handle real attributes by treating items as (attribute, value) pairs, where the value is not the original one, but is perturbed by a small amount and is a range based value. We also propose our own similarity measure which captures the nature of real valued attributes and provide effective weights for the itemsets. The probabilistic contributions of different itemsets is taken into considerations during classification. Some of the applications where such a technique is useful are in signal classification, medical diagnosis and handwriting recognition. Experiments conducted on the UCI Repository datasets show that PERFICT is highly competitive in terms of accuracy in comparison with popular associative classification methods.

关键词： Itemsets Histograms Training Probabilistic logic Data mining Estimation Weight measurement

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Continuous Search in Constraint programming

Continuous Search in Constraint Programming

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Alejandro Arbelaez Youssef Hamadi Michele Sebag Microsoft-INRIA Joint Laboratory Orsay France Microsoft Research Limited Cambridge UK LIX École Polytechnique Palaiseau France Project-team TAO INRIA Saclay Île-de-France LRI (UMR CNRS 8623) Orsay France

This work presents the concept of Continuous Search (CS), which objective is to allow any user to eventually get their constraint solver achieving a top performance on their problems. Continuous Search comes in two modes: the functioning mode solves the user's problem instances using the current heuristics model; the exploration mode reuses these instances to train and improve the heuristics model through Machine Learning during the computer idle time. Contrasting with previous approaches, Continuous Search thus does not require that the representative instances needed to train a good heuristics model be available beforehand. It achieves lifelong learning, gradually becoming an expert on the user's problem instance distribution. Experimental validation suggests that Continuous Search can design efficient mixed strategies after considering a moderate number of problem instances.

关键词： Training Search problems Support vector machines Computational modeling Production Kernel Runtime

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Language Model Combination for Community-based Q & A Retrieval

Language Model Combination for Community-based Q & A Retriev...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Akira Takahashi Atsuhiro Takasu Jun Adachi University of Tokyo Tokyo Japan National Institute of Information and Communications Technology Tokyo Japan

This paper proposes three methods for combining various probabilistic models for retrieving answers from community-based question answering (cQA) archives. We adopt four probabilistic models for these combinations, i.e., (1) the language model measuring similarity between a query and a question stored in the cQA archive, (2) two translation models for measuring the similarity between a query and an answer stored in the cQA archive, and a background language model for smoothing. Then, we developed three parameter estimation methods. Two of them are mixture models of the language models. The remaining model exploits the difference between the models. We apply the proposed methods to a cQA archive and show that they significantly outperform a widely used language model and Okapi BM25. We also show that they achieve a better performance than the recently proposed cQA retrieval method.

关键词： Probabilistic logic Data models Information retrieval Convergence Internet Electronic mail Graphical models

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Hybrid Intelligent Design of Morphological-Rank-Linear Perceptrons for Software Development Cost Estimation

Hybrid Intelligent Design of Morphological-Rank-Linear Perce...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Ricardo de A. Araújo Adriano L.I. de Oliveira Sergio Soares Nat. Inst. of Sci. & Technol. for Software Eng. Recife Brazil National Institute of Science and Technology for Software Engineering Recife PE Brazil Informatics Center Federal University of Pernambuco Recife PE Brazil

This paper presents a hybrid intelligent method to design Morphological-Rank-Linear (MRL) perceptrons to solve the Software Development Cost Estimation (SDCE) problem. The proposed method uses a modified genetic algorithm (MGA) to determine the best particular features to improve the MRL perceptron performance, as well as its initial parameters. Furthermore, for each individual of MGA, a gradient steepest descent method is used to optimize the MRL perceptron parameters supplied by MGA. An experimental analysis is conducted with the proposed method using the Desharnais and Cocomo databases. In the experiments, two relevant performance metrics and a fitness function are used to assess the performance of the proposed method. The results obtained are compared to methods recently presented in literature.

关键词： Software Estimation programming Measurement Equations Training Databases

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Gaussian Processes with OAD Covariance Function for Hyperspectral Data Classification

Gaussian Processes with OAD Covariance Function for Hyperspe...

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international conference on Tools for Artificial Intelligence (ICTAI)

作者： Sven Schneider Arman Melkumyan Richard J. Murphy Eric Nettleton Australian Centre for Field Robotics School of AeroSpace Mechanical and Mechatronic Engineering University of Sydney NSW Australia

A new method is presented which combines a deterministic analytical method and a probabilistic measure to classify rock types on the basis of their hyperspectral curve shape. This method is a supervised learning algorithm using Gaussian Processes (GPs) and the Observation Angle Dependent (OAD) covariance function. The OAD covariance function makes use of the properties of the Spectral Angle Mapper (SAM) which is used frequently for classifying hyperspectral data. Results show that it is possible to identify and classify rocks in an `One vs. One' and an `One vs. All' approach using the entire spectral curve (0.35-2.5 μm). The results show an average classification accuracy of 98% and an F-score of 92% for the new method in an `One vs. All' approach. Slightly higher classification accuracy and F-measure for the new method can be achieved for the `One vs. One' binary approach. This paper extends the ideas of the deterministic SAM method to a probabilistic framework and enables data fusion with similar and disparate kinds of sensors. This paper demonstrates a superior classification performance of the new probabilistic method over the classical SAM.

关键词： Accuracy Probabilistic logic Uncertainty Hyperspectral imaging Libraries Shape

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logic Gates Based on Carbon Nanotube Field-Effect Transistors with SiN_x Passivation Films

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JAPANESE JOURNAL OF APPLIED PHYSICS 2010年第6期49卷 06GG021-06GG024页

作者： Kishimoto, Takaomi Ohno, Yasuhide Maehashi, Kenzo Inoue, Koichi Matsumoto, Kazuhiko Osaka Univ Inst Sci & Ind Res Osaka 5670047 Japan

We demonstrated logic gates based on complementary carbon nanotube field-effect transistors (CNT-FETs) with SiNx passivation films deposited by catalytic chemical vapor deposition. The carrier type of CNT-FETs was controlled by forming SiNx passivation films. Electrical measurements revealed that the p-type characteristics of CNT-FETs were converted to n-type characteristics after the deposition of SiNx passivation films. Then, the n-type CNT-FETs with SiNx passivation films were reconverted to p-type CNT-FETs by annealing in N-2 atmosphere. As a consequence, complementary voltage inverters comprising p-and n-type CNT-FETs with SiNx passivation films were demonstrated on the same SiO2 substrate by conventional photolithography and lift-off techniques. Moreover, the static transfer and dynamic characteristics of the CNT-FET-based inverters were investigated. It was found that a gain of approximately 3 was achieved and that the device was switched properly at frequencies of up to 100 Hz. (C) 2010 The Japan Society of Applied Physics

关键词： Silica

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Coinductive logic programming and its application to boolean SAT

Coinductive logic programming and its application to boolean...

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22nd international Florida Artificial Intelligence Research Society conference, FLAIRS-22

作者： Min, Richard Gupta, Gopal Department of Computer Science University of Texas at Dallas Richardson TX United States

ISBN: (纸本)9781577354192

Coinduction has recently been introduced into logic programming by Simon et al. The resulting paradigm, termed coinductive logic programming (co-LP), allows one to model and reason about infinite processes and objects. Co-LP extended with negation has many interesting applications: for instance in developing top-down, goal-directed evaluation strategies for Answer Set programming. In this paper we show yet another application of co-LP, namely, elegantly realizing Boolean SAT solvers. Copyright © 2009, Assocation for the Advancement of ArtdicaI Intelligence (***). All rights reserved.

关键词： logic programming

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