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IEEE International Conference on systems, Man and Cybernetics

作者： A. Harati M.N. Ahmadabadi Institute for Studies on Theoretical Physics and Mathematics School of Intelligent Systems Tehran Iran Robotics and AI Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Q-learning is widely used in many multi agent systems. In most cases, a separate critic is considered for qualifying each individual agent behavior or it is assumed that the critic is completely aware of effects of all agents' actions on the team qualification. But, in many cases, the role of each team member in the group performance is not known. In order to distribute a common credit among the agents, a suitable criterion must be provided to estimate the role of each agent in the team performance and to judge if an agent has done a wrong action. In this paper two such criteria, named certainty and expertness, for a team of agents with parallel tasks are introduced. In addition, two methods for reinforcing the agents based on the proposed measures are provided. Some simulation results are also reported to show the effectiveness of the proposed measures and methods.

关键词： intelligent agent Learning systems Multiagent systems intelligent sensors Artificial intelligence Laboratories intelligent systems intelligent robots Physics Mathematics

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ROBUST CONGESTION CONTROL IN HIGH SPEED COMMUNICATION NETWORKS: A MODEL PREDICTIVE CONTROL APPROACH

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IFAC Proceedings Volumes 2002年第1期35卷 103-108页

作者： Hua O. Wang Yongru Gu Huajing Fang Laboratory for Intelligent and Nonlinear Control (LINC) Department of Electrical and Computer Engineering Duke University Durham NC 27708-0291 USA Center for Nonlinear and Complex Systems Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

In this paper, the design of explicit rate-based congestion control in high speed communication networks is considered. At a bottleneck node, there are multiple best-effort sources competing with other high priority cross traffic sources. The goal of congestion control is to achieve high link utilization, low packet loss, low delay, and fairness among the best-effort sources. In this paper, the high priority traffic is described by an autoregressive integrated moving average (ARIMA) process. To deal with the propagation delays associated with the best-effort sources, model predictive control, particularly, generalized predictive control, techniques are proposed to solve the congestion problem here. It is demonstrated that the proposed controller performs well and is robust to delay uncertainties. In addition, in a multiple-nodes configuration, the controller provides max-min fairness.

关键词： Communication control applications Model-based control Predictive control Communication networks Time delay Robustness

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A NEURAL COMPUTATION MODEL FOR REAL-TIME COLLISION-FREE ROBOT NAVIGATION

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IFAC Proceedings Volumes 2002年第1期35卷 323-328页

作者： Simon X. Yang Max Meng Hao Li Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering University of Guelph Guelph ON N1G 2W1 Canada Advanced Robotics and Teleoperation (ART) Lab Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2G7 Canada

A biologically inspired neural computation model is proposed for dynamic planning and tracking control of robots. The dynamic environment is represented by a neural activity landscape of a topologically organized neural network, where each neuron is characterized by a shunting equation. The collision-free path is generated in real-time through the activity landscape without any prior knowledge of the dynamic environment. The real-time tracking control of robots to follow the planned path is also designed using shunting equations. The effectiveness is demonstrated through case studies. Simulation in several computer-synthesized virtual environments further demonstrates the advantages of the proposed approach.

关键词： path planning obstacle avoidance velocity control neural dynamics neural network

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Reducing pronunciation lexicon confusion and using more data without phonetic transcription for pronunciation modeling 7

Reducing pronunciation lexicon confusion and using more data...

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7th International Conference on Spoken Language Processing, ICSLP 2002

作者： Zheng, Fang Song, Zhanjiang Fung, Pascale Byrne, William Center of Speech Technology State Key Lab of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua Univ. Beijing100084 China Department of Electrical and Electronic Engineering Hong Kong Univ. of Science and Technology Hong Kong Center for Language and Speech Processing Johns Hopkins Univ. United States Beijing D-Ear Technologies Co. Ltd. China

The multiple-pronunciation lexicon (MPL) is very important to model the pronunciation variations for spontaneous speech recognition. But the introduction of MPL brings out two problems. First, the MPL will increase the among-lexicon confusion and degrade the recognizer's performance. Second, the MPL needs more data with phonetic transcription so as to cover as many surface forms as possible. Accordingly, two solutions are proposed, they are the context-dependent weighting method and the iterative forced-alignment based transcription method. The use of them can compensate what the MPL causes and improve the overall performance. Experiments across a naturally spontaneous speech database show that the proposed methods are effective and better than other methods.

关键词： Iterative methods

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An efficient approach of the SOM algorithm to the traveling salesman problem

An efficient approach of the SOM algorithm to the traveling ...

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Brazilian Symposium on Neural Networks

作者： F. Vieira A. Neto J. Costa Computer Engineering and Automation Department Technological Center Intelligent Systems Laboratory Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Electrical Engineering Department Intelligent Systems Laboratory Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil

This paper presents an approach to the well-known traveling salesman problem (TSP) via competitive neural networks. The neural network model adopted in this work is the Kohonen network or self-organizing maps (SOM), which has important topological information about its neurons configuration. This paper is concerned with the initialization aspects, parameters adaptation, and the complexity analysis of the proposed algorithm. The modified SOM algorithm proposed in this paper has shown better results when compared with others neural network based approaches to the TSP.

关键词： Traveling salesman problems Neurons Neural networks Cities and towns Convergence Joining processes Automation intelligent systems Self organizing feature maps Algorithm design and analysis

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A new model of the visual feedback coordinate transformation in humans based on disturbance noise and feedback error that accounts for time delays

A new model of the visual feedback coordinate transformation...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： E. Oyama K.F. MacDorman T. Maeda S. Tachi A. Agah Science and Technology (AIST) National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan Intelligent Robotics Laboratory Graduate School of Systems Engineering Wakayama University Wakayama Japan School of Engineering University of Tokyo Bunkyo Tokyo Japan Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

An essential factor in understanding the motor learning capability of humans, is the coordinate transformation learning of the visual feedback controller. Although a number of learning models for the visual feedback controller have been proposed, none has been able to establish a definitive approach. In our previous work, we have suggested a learning model that uses disturbance noise and the feedback error signal to learn the human visual feedback controller's coordinate transformation. However, the model does not fully consider the time delay in the visual feedback control loop. This paper presents a modified learning model taking into account the time delay and the convergence properties of the model. Numerical simulations are presented to illustrate the effectiveness of the proposed approach.

关键词： Humans Delay effects Adaptive control Error correction Biological system modeling Feedback control Convergence Kinematics intelligent robots Velocity control

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Using Motives and Artificial Emotions for Prolonged Activity of a Group of Autonomous Robots

Using Motives and Artificial Emotions for Prolonged Activity...

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2001 AAAI Fall Symposium

作者： Michaud, François Robichaud, Etienne Audet, Jonathan LABORIUS - Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical and Computer Engineering Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada

To operate over a long period of time in the real world, autonomous mobile robots must have the capability of recharging themselves whenever necessary. In addition to be able to find and dock into a charging station, robots must be able to decide when and for how long to recharge. This decision is influenced by the energetic capacity of their batteries and the contingencies of the environment. To deal with this temporality issue and using research evidences from the field of psychology, this study investigates the use of motives and artificial emotions to regulate the recharging need of autonomous robots. © 2001 AI Access Foundation. All rights reserved.

关键词： Robots

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Finding objects in a 3D environment by combining distance measurement and color indexing

Finding objects in a 3D environment by combining distance me...

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IEEE International Conference on Image Processing

作者： A. Koschan SunHo Lee M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee USA

A new method is presented for the localization and recognition of three-dimensional objects using color information. In the first processing step, we estimate depth information by either applying a chromatic block matching method to color stereo images or acquiring a range image from a laser scanner. Second, the computed depth maps are segmented to distinguish between the image background and the objects that should be recognized. Assuming that the segmented regions represent single objects in the three-dimensional scene, feature vectors are generated based on color histograms. The Euclidean distance is used as well as the scalar product to measure the similarity between the feature vectors computed from the color image and the feature vectors stored in a database.

关键词： Distance measurement Indexing Color Histograms Image recognition Image segmentation Colored noise Layout Lighting intelligent robots

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Fast target classification using sonar

Fast target classification using sonar

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： A. Heale L. Kleeman Intelligent Robotics Research Centre Department of Electrical and Computer Systems Engineering Monash University VIC Australia

This paper describes a new sonar system that can perform target localisation in two dimensions and classification into planes, concave corners and convex edges with no extra time overhead, that is, the sensor transmits on two transmitters a short time apart, thereby collecting echoes in virtually the same time as a single transmitter of the system. Moreover, the time separation of the transmitted pulses acts to identify the particular sonar system so that interference from other systems can be rejected. The sensor combines two previous sonar research efforts on double pulse coding and classification in a real time DSP-based sensing module that is also smaller than previous sensors. Since the classification is performed with such a short delay between transmitter firings, the sensor can be deployed on moving platforms to achieve on-the-fly mapping. This paper describes the sonar hardware, maximum likelihood estimation classification approach and experimental results.

关键词： Transmitters Interference Maximum likelihood estimation Delay Sonar measurements Coordinate measuring machines intelligent robots Robot sensing systems Digital signal processing Hardware

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Light signaling for social interaction with mobile robots

Light signaling for social interaction with mobile robots

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： F. Michaud Minh Tuan Vu Laborius-Research Laboratory on Mobile Robotics and Intelligent Systems Department of Electrical and Computer Engineering Université de Sherbrook Sherbrooke QUE Canada

To give autonomous mobile robots some kind of "social intelligence", they need to be able to recognize and interact with other agents in the world. This paper describes how a light signaling device can be used to identify another individual and to communicate simple information. By having the agents relatively close to each other, they share the same perceptual space, which allows them to sense or deduce implicit information concerning the context of their interaction. Using a vision- and sonar-based Pioneer I robot equipped with a colored-light signaling device, experimental results demonstrate how the robot. can interact with a human interlocutor in a ball-passing game.

关键词： Mobile robots intelligent robots intelligent agent Human robot interaction Humanoid robots Robot sensing systems Orbital robotics Animals Robot vision systems Protocols

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