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IEEE/RSJ International Conference on intelligent robotics and systems

作者： Moritz Tenorth Michael Beetz Intelligent Robotics and Communications Lab ATR Kyoto Japan Intelligent Autonomous Systems/Artificial Intelligence Department of Computer Science and Centre for Computing Technologies (TZI) University of Bremen Germany

ISBN: (纸本)9781467317375

Mobile manipulation robots are becoming more and more common and begin to extend their task spectrum towards more general housework activities. The sequence of actions needed to accomplish such tasks can be obtained from instructions on the Internet originally written for humans. While giving valuable information about the types of actions and some of their parameters, these instructions usually lack information that humans consider to be obvious. In this paper, we investigate how we can equip robots with sufficient knowledge and inference mechanisms to competently detect and fill such knowledge gaps in descriptions of everyday activities. We present methods for projecting the effects of actions and processes, for inferring action parameters like the objects and locations to be used, and introduce representations for reasoning about object transformations resulting from the effects of actions.

关键词： their Effects some introduce representations Reasoning Robot Action EFFECTS OF THE ACTION Inference mechanisms instruction Human information-type

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A Handy Image Explorer with Tactile Feedback for Diagnostic Imaging

A Handy Image Explorer with Tactile Feedback for Diagnostic ...

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International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

作者： Jiaqing Lin Hiroaki Nishino Tsuneo Kagawa Kouichi Utsumiya Department of Computer Science and Intelligent Systems Oita University Japan Institute for Hypernerwork Society Oita Japan

Diagnostic imaging with tracing a series of CT scan images is an important way for doctors to detect lesions. The doctors, however, need to view a huge number of high resolution images in a day, therefore, excessive burdens on their vision become a very serious problem. We propose a new method of assisting the diagnostic imaging with a multimodal interaction technique. We designed and prototyped a system allowing users (doctors) to stably exploring and finding critical features observed in the medical images even if they get eye strain. The system supports sound and hap tic modalities for assisting the users' vision to find important parts that cannot be overlooked in the images. It extracts some visual features observed in the images and transforms them to other sensory parameters. Then, the system notifies the doctors for possible existence of lesions in the images with multiple sensory outputs. This paper especially presents a method to use hap tic modality, the sense of touch, as a sensory channel for calling the users' attention to focus on some specific parts in an image. We also show mobile tablet personal computers (PCs) are promising hardware platform to implement the system.

关键词： Haptic interfaces Vibrations Medical services Feature extraction Computed tomography Medical diagnostic imaging

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Movement segmentation and recognition for imitation learning 15

Movement segmentation and recognition for imitation learning

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15th International Conference on Artificial Intelligence and Statistics, AISTATS 2012

作者： Meier, Franziska Theodorou, Evangelos Schaal, Stefan Computational Learning and Motor Control Lab University of Southern California Los Angeles United States Department of Computer Science and Engineering University of Washington Seattle United States Max-Planck-Institute for Intelligent Systems Tübingen Germany

In human movement learning, it is most common to teach constituent elements of complex movements in isolation, before chaining them into complex movements. Segmentation and recognition of observed movement could thus proceed out of this existing knowledge, which is directly compatible with movement generation. In this paper, we address exactly this scenario. We assume that a library of movement primitives has already been taught, and we wish to identify elements of the library in a complex motor act, where the individual elements have been smoothed together, and, occasionally, there might be a movement segment that is not in our library yet. We employ a flexible machine learning representation of movement primitives based on learnable nonlinear attractor system. For the purpose of movement segmentation and recognition, it is possible to reformulate this representation as a controlled linear dynamical system. An Expectation-Maximization algorithm can be developed to estimate the open parameters of a movement primitive from the library, using as input an observed trajectory piece. If no matching primitive from the library can be found, a new primitive is created. This process allows a straightforward sequential segmentation of observed movement into known and new primitives, which are suitable for robot imitation learning. We illustrate our approach with synthetic examples and data collected from human movement.

关键词： Maximum principle

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ADMM For Consensus On Colored Networks

ADMM For Consensus On Colored Networks

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IEEE Annual Conference on Decision and Control

作者： Joao F. C. Mota Joao M. F. Xavier Pedro M. Q. Aguiar Markus Puschel Department of Electrical and Computer Engineering Carnegie Mellon University Institute of Systems and Robotics Instituto Superior Tecnico Technical University of Lisbon Department of Computer Science

ISBN: (纸本)9781467320658

We propose a novel distributed algorithm for one of the most fundamental problems in networks: the average consensus. We view the average consensus as an optimization problem, which allows us to use recent techniques and results from the optimization area. Based on the assumption that a coloring scheme of the network is available, we derive a decentralized, asynchronous, and communication-efficient algorithm that is based on the Alternating Direction Method of Multipliers (ADMM). Our simulations with other state-of-the-art consensus algorithms show that the proposed algorithm is the one exhibiting the most stable performance across several network models.

关键词： distributed algorithms Network network model simulating

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Global analytic solution of fully-observed variational Bayesian matrix factorization

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The Journal of Machine Learning Research 2013年第1期14卷

作者： Kevin Murphy Bernhard Schölkopf Shinichi Nakajima Masashi Sugiyama S. Derin Babacan Ryota Tomioka Google MPI for Intelligent Systems Optical Research Laboratory Nikon Corporation Tokyo Japan Department of Computer Science Tokyo Institute of Technology Tokyo Japan Beckman Institute University of Illinois at Urbana-Champaign Urbana IL Department of Mathematical Informatics The University of Tokyo Tokyo Japan

The variational Bayesian (VB) approximation is known to be a promising approach to Bayesian estimation, when the rigorous calculation of the Bayes posterior is intractable. The VB approximation has been successfully applied to matrix factorization (MF), offering automatic dimensionality selection for principal component analysis. Generally, finding the VB solution is a nonconvex problem, and most methods rely on a local search algorithm derived through a standard procedure for the VB approximation. In this paper, we show that a better option is available for fully-observed VBMF--the global solution can be analytically computed. More specifically, the global solution is a reweighted SVD of the observed matrix, and each weight can be obtained by solving a quartic equation with its coefficients being functions of the observed singular value. We further show that the global optimal solution of empirical VBMF (where hyperparameters are also learned from data) can also be analytically computed. We illustrate the usefulness of our results through experiments in multi-variate analysis.

关键词： empirical bayes matrix factorization model-induced regularization probabilistic PCA variational bayes

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A Tangible Information Explorer Using Vibratory Touch Screen

A Tangible Information Explorer Using Vibratory Touch Screen

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Hiroaki Nishino Yuki Fukakusa Akari Hatano Tsuneo Kagawa Kouichi Utsumiya Department of Computer Science and Intelligent Systems Oita University Oita Japan Institute for Hypernetwork Society Oita Japan

Touch panel displays are becoming available for implementing futuristic human computer interaction (HCI) methods and are proven to be a useful infrastructure for creating intuitive HCI. In spite of their popularity, there are some drawbacks. The most serious one is their hardness to operate especially for the weak in information technology such as elderly and blind users. A tactile feedback function has a potential ability for enabling them to make full use of the devices. We propose an approach for effectively designing user-friendly HCI based on the tactile feedback. We exemplify our approach through the design and development of a practical application, a haptic web browser. It allows even the weak users to intuitively explore various web pages without heavily depending on the visual information. While the system targets at supporting the weak, the touch interactions are quite useful means for general public to improve the stability and the degree of satisfaction in web browsing operations. The proposed system uses a touch panel haptic display for helping the users to operate with intuitive touch sensations.

关键词： Browsers Web pages Tactile sensors Graphical user interfaces Force feedback Vibrations

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Interactive concept maps and learning outcomes in Guru

Interactive concept maps and learning outcomes in Guru

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25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

作者： Person, Natalie Olney, Andrew D'Mello, Sidney Lehman, Blair Department of Psychology Rhodes College Memphis TN 38152 United States Institute for Intelligent Systems University of Memphis Memphis TN 38152 United States Departments of Psychology and Computer Science University of Notre Dame South Bend IN 46556 United States

ISBN: (纸本)9781577355588

Concept maps are frequently used in K-12 educational settings. The purpose of this study is to determine whether students' performance on interactive concept map tasks in Guru, an intelligent tutoring system, is related to immediate and delayed learning outcomes. Guru is a dialogue-based system for high-school biology that intersperses concept map tasks within the tutorial dialogue. Results indicated that when students first attempt to complete concept maps, time spent on the maps may be a good indicator of their understanding, whereas the errors they make on their second attempts with the maps may be an indicator of the knowledge they are lacking. This pattern of results was observed for one cycle of testing, but not replicated in a second cycle. Differences in the findings for the two testing cycles are most likely due to topic variations. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： computer aided instruction

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How do they do it? Investigating dialogue moves within dialogue modes in expert human tutoring

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11th International Conference on intelligent Tutoring systems, ITS 2012

作者： Lehman, Blair D'Mello, Sidney Cade, Whitney Person, Natalie Institute for Intelligent Systems University of Memphis Memphis TN 38152 United States Departments of Psychology and Computer Science University of Notre Dame Notre Dame IN 46556 United States Department of Psychology Rhodes College Memphis TN 38112 United States

ISBN: (纸本)9783642309496

Expert human tutors are widely considered to be the gold standard for increasing student learning. While not every student has access to an expert tutor, it is possible to model intelligent tutoring systems after expert tutors. In an effort to achieve this goal, we have analyzed a corpus of 50 hours of one-to-one expert human tutoring sessions. This corpus was coded for speech acts (dialogue moves) and larger pedagogical strategies (dialogue modes). Using mixed-effects modeling, we found that expert tutors differentially used dialogue moves depending on the dialogue mode. Specifically, tutor posed questions, explanations, and motivational statements were predictive of different dialogue modes (e.g., Lecture, Scaffolding). © 2012 Springer-Verlag.

关键词： computer aided instruction

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Distributed ADMM for Model Predictive Control and Congestion Control

Distributed ADMM for Model Predictive Control and Congestion...

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IEEE Annual Conference on Decision and Control

ISBN: (纸本)9781467320658

Many problems in control can be modeled as an optimization problem over a network of nodes. Solving them with distributed algorithms provides advantages over centralized solutions, such as privacy and the ability to process data locally. In this paper, we solve optimization problems in networks where each node requires only partial knowledge of the problem's solution. We explore this feature to design a decentralized algorithm that allows a significant reduction in the total number of communications. Our algorithm is based on the Alternating Direction of Multipliers (ADMM), and we apply it to distributed Model Predictive Control (MPC) and TCP/IP congestion control. Simulation results show that the proposed algorithm requires less communications than previous work for the same solution accuracy.

关键词： distributed model predictive control Communication Research PROBLEM SOLUTION Model predictive control Predictive control distributed algorithms Privacy nonlinear model predictive control Batch data processing control simulation Solutions Standing Orders Ganglia

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AI@NICTA

AI@NICTA

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作者： Barnes, Nick Baumgartner, Peter Caetano, Tiberio Durrant-Whyte, Hugh Klein, Gerwin Sanderson, Penelope Sattar, Abdul Stuckey, Peter Thiebaux, Sylvie Van Hentenryck, Pascal Walsh, Toby NICTA Australia Software Systems Research Group NICTA Australia Machine Learning Research Group NICTA Australia Trustworthy Systems Project NICTA Australia University of Queensland Australia Institute for Integrated and Intelligent Systems Griffith University Australia Department of Computing and Information Systems University of Melbourne Australia School of Computer Science Australian National University Australia Melbourne School of Engineering Australia

National Information and Communications Technology Australia (NICTA) is the largest ICT research center in Australia, having been established 10 years ago in 2002. It has five laboratories in four Australian capital cities: Sydney, Canberra, Melbourne, and Brisbane. There are currently around 700 staff and Ph.D. students working at NICTA. In June 2009, the 100th Ph.D. student to study at NICTA graduated. At present and averaged over the year, one new Ph.D. student studying at NICTA graduates every 10 days. NICTA has close links with its university members (Australian National University, the University of New South Wales, and the University of Melbourne) as well as with its partner universities (University of Sydney, Griffith University, Queensland University of Technology, University of Queensland, and most recently Monash University). Many of the researchers at NICTA are seconded from these universities. In addition, most of the other researchers at NICTA hold adjunct positions at one of these universities, enabling them to teach courses and supervise Ph.D. students. NICTA also has close links with a number of other research organizations (including Australia's CSIRO, France's INRIA, Japan's NII, and Germany's Fraunhofer institute) and major companies (including Microsoft, Google, SAP, and Ericsson). Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Students

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