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检索条件"机构=Department of Computer Science Institute for Robotics and Intelligent Systems"

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Optimum complexity neural networks for anomaly detection task

Optimum complexity neural networks for anomaly detection tas...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： R. Kozma N.S. Majumdar D. Dasgupta Division of Computer Science Institute for Intelligent Systems Department of Mathematical Sciences University of Memphis TN USA

In this paper we study the performance of compressed data for classification and anomaly detection. We use networks of various complexities for our purpose, guided by the data itself rather than one uniform-complexity... 详细信息

关键词： Neural networks Testing Nearest neighbor searches Data compression Niobium computer science intelligent systems Degradation Performance evaluation

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Exploring the performance of an evolutionary algorithm for greenhouse control

Exploring the performance of an evolutionary algorithm for g...

引用

International Conference on Information Technology Interfaces

作者： R.K. Ursem B. Filipic T. Krink Department of Computer Science University of Aarhus Aarhus Denmark Department of Intelligent Systems Jozef Stefan Institute Ljubljana Slovenia

Evolutionary algorithms for optimization of dynamic problems have recently received increasing attention. Online control is a particularly interesting class of dynamic problems, because of the interactions between the controller and the controlled system. In this paper, we report experimental results on two aspects of the direct control strategy in relation to a crop-producing greenhouse. In the first set of experiments, we investigated how to balance the available computation time between population size and generations. The second experiments were on different control horizons, and showed the importance of this aspect for direct control. Finally, we discuss the results in the wider context of dynamic optimization.

关键词： Evolutionary computation Control systems computer science Three-term control Computational modeling intelligent systems Constraint optimization Temperature dependence Testing Process design

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H/sub 2/ control for uncertain time-delay fuzzy systems

H/sub 2/ control for uncertain time-delay fuzzy systems

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IEEE International Conference on systems, Man and Cybernetics

作者： Huaping Liu Fuchun Sun Kezhong He Zengqi Sun Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing China Robotics Laboratory Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China

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Distributed problem solving and the boundaries of self-configuration in multi-hop wireless networks

Distributed problem solving and the boundaries of self-confi...

引用

Annual Hawaii International Conference on System sciences (HICSS)

作者： B. Krishnamachari R. Bejar S. Wicker School of Electrical and Computer Engineering USA Intelligent Information Systems Institute Department of Computer Science Cornell University Ithaca NY USA

ISBN: (纸本)0769514359

We consider three distributed decision making tasks that arise in the design and configuration of multi-hop wireless networks: medium access scheduling, Hamiltonian cycle formation, and the partitioning of network nodes into coordinating cliques. We first model these tasks as distributed constraint satisfaction problems (DCSPs). We show that the communication complexity of DCSPs can be related to the computational complexity of centralized constraint satisfaction problems. We then use centralized algorithms to obtain experimental results on the solvability and complexity of the three DCSPs. We show that these problems exhibit "phase transitions" in solvability and complexity as the transmission power of the wireless nodes is varied. Based on these results, we argue that phase transition analysis provides a mechanism for quantifying the critical range of network resources needed for scalable, self-configuring multi-hop wireless networks.

关键词： Problem-solving intelligent networks Spread spectrum communication Wireless networks Computational complexity Network topology Transmitters computer networks Distributed computing systems engineering and theory

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Integrating ground and aerial views for urban site modeling

Integrating ground and aerial views for urban site modeling

引用

International Conference on Pattern Recognition

作者： Sung Chun Lee Soon Ki Jung R. Nevatia Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA Department of Computer Engineering Kyungpook National University Daegu South Korea

ISBN: (纸本)076951695X

3D models of urban sites with good geometry and facade textures are needed for many planning and visualization applications. Approximate wireframe can be derived from aerial images but detailed textures must be obtained from ground level images. Integrating such views with the 3D models is difficult as only small parts of buildings may be visible in a single view. We describe a method that uses two or three vanishing points, not necessarily from orthogonal sets of parallel lines, and a small number of point correspondences to estimate the intrinsic and extrinsic parameters of the ground level cameras. Experimental results from some buildings are presented.

关键词： Buildings Cameras intelligent robots Solid modeling Urban planning Urban areas intelligent systems Computational geometry Application software Data visualization

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An extension of weighted strategy sharing in cooperative Q-learning for specialized agents

An extension of weighted strategy sharing in cooperative Q-l...

引用

International Conference on Neural Information Processing

作者： S.M. Eshgh M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rides for unseen situations. These benefits will be gained if the learning agents know the area of expertise and the expertness values of each other. In this paper, some Q-learning agents with different skills and expertness levels cooperate in learning. The agents use some criteria to judge others information and knowledge. Four expertness criterion, certainty and entropy measures are used to assign degrees of importance to others' Q-Tables. Effects of measuring these values based on their whole Q-Table, a portion of Q-Tables that reflects their proficiencies, and the states in Q-Tables on the learning quality are studied. Simple strategy sharing and two different weighted strategy-sharing methods are used to combine the acquired knowledge from different agents.

关键词： intelligent robots intelligent agent Process control Control systems intelligent control Laboratories intelligent systems Physics Mathematics Entropy

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A neural approach to an attentive navigation for 3D intelligent virtual agents

A neural approach to an attentive navigation for 3D intellig...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： M. Lozano J. Molina Artec Group Institute of Robotics. Computer Science Department University of Valencia Valencia Spain Neurotechnology Control and Robotics Group Engineering and Automatic Systems Department Politechnic University of Cartagena Spain

This paper presents an attempt to integrate attention and navigation skills in 3D embodied agents (virtual humanoids). The neural model presented has been divided in two main phases. Firstly the environment-categorization phase, where an online pattern recognition and categorization of the agent current sensory input data is carried out by an adaptive resonance driven self organizing neural network, which will finally simulate the agent's short term memory (STM). Secondly, the model must also learn how and when to map its current STM state into the navigation and attention motor layers of the 3D agent. We also review the world modelling and the agent vision system, and finally we present the first results extracted from two of the subsystems which conforms the complete neural model, such as, the environment categorization subsystem and the base navigation neural model.

关键词： Navigation intelligent agent intelligent robots robotics and automation Humans Graphics Virtual environment Machine vision computer science Augmented virtuality

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Cooperative Q-learning with heterogeneity in actions

Cooperative Q-learning with heterogeneity in actions

引用

IEEE International Conference on systems, Man and Cybernetics

作者： S.M. Reza MirFattah 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

Cooperation in learning improves the speed of convergence and the quality of learning. Special care is needed when heterogeneous agents cooperate in learning. It is discussed that, cooperation in learning may cause the learning process to diverge if heterogeneity is not handled properly. In this paper, it is assumed that two heterogeneous Q-learning agents cooperate to learn. The heterogeneity is assumed in their action order (and not in their action set). A Q-learning-based method is introduced for the agents to learn the mapping among their actions. It is shown that, the agents are able to learn this mapping while cooperating in learning. Some simulation results are reported to show the effectiveness of the proposed method.

关键词： intelligent agent intelligent robots Humans Telecommunication control Artificial intelligence Laboratories intelligent systems Physics Mathematics Convergence

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A new approach to credit assignment in a team of cooperative Q-learning agents

A new approach to credit assignment in a team of cooperative...

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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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Certainty and expertness-based credit assignment for cooperative Q-Learning agents with an AND-type task

Certainty and expertness-based credit assignment for coopera...

引用

International Conference on Neural Information Processing

作者： A. Harati M.N. Ahmadabadi School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence & AI and Robotics Laboratory Department of Electrical and Computer Engineering University of Tehran Tehran Iran

In multiagent reinforcement learning, inter-agent credit assignment is a fundamental problem, since a single scalar reinforcement signal is the only reliable feedback that teams of learning agents receive. This problem is more critical in groups of independent learners with a joint task. In this research, it is assumed that a critic agent receives the environment feedback and assigns a proper credit to each agent using some measures. Three of such measures for a team of cooperative agents with a parallel and AND-type task are introduced. These measures somehow compare the agents' knowledge. One of these criteria, called normal expertness, is a non-relative measure while two other ones (certainty and relative normal expertness) are relative measure. It is experimentally shown that relative measures work better as they contain more information for the critic agent.

关键词： Feedback intelligent agent intelligent robots Process control Control systems intelligent control Artificial intelligence Robot kinematics Physics computing Reliability engineering

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