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Learning Cooperative Object Pushing with Variable Contact Point

Learning Cooperative Object Pushing with Variable Contact Po...

引用

2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Pages 805-1210

作者： Abdol Hossein Aminaiee Majid Nili Ahmadabadi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence Department of Electerical and Computer Engineering University of Tehran

ISBN: (纸本)9781424412631;1424412633

Learning in multi-agent environments where each agent's action directly affects other agents would be an important matter and a complicated task. To reduce the learning time and simplifying the learning process, it is suitable to learn individual skills and then provide cooperation and coordination utilizing the learned individual skills. In the approach proposed in this paper, agents benefit from their individual knowledge obtained in the individual learning phase to cooperate with other agents. Cooperative object pushing system is used as a testbed to our proposed method where cooperation and coordination between agents are needed in these systems. Agents independently learn to push the object to the target by using the proposed fuzzy reinforcement learning method. Agents attain their cooperative behaviors properly making use of the coded knowledge in the Q-table. Simulation and experimental results show that by interpreting the knowledge in the Q-table, agents can achieve high level behaviors with a high degree of cooperation.

关键词： Agents Learning Point contacts pushing variable contact

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Basic Movements of a Nonholonomic Wheel-Based Pole Climbing Robot

Basic Movements of a Nonholonomic Wheel-Based Pole Climbing ...

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2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Pages 805-1210

作者： Sara Mahdavi Ehsan Noohi Majid Nili Ahmadabadi Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)9781424412631;1424412633

Three basic movements for path planning of a nonholonomic wheel-based pole climbing robot, UT-PCR, are proposed. In order to simplify the system equations, the state equations are first derived in the velocity space in which the nonholonomic constraint is easily shown. Subsequently, according to the derived equations, three basic movements are defined and a suitable control method is proposed. Finally, the proposed movements and the control method are tested via simulations.

关键词： Climbing Robot Nonholonomic Systems Basic Movements

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Designing a home security system using sensor data fusion with DST and DSmT methods

Designing a home security system using sensor data fusion wi...

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FUSION 2007 - 2007 10th International Conference on Information Fusion

作者： Behzad Moshiri Khalkhali, Arezou Moussavi Reza Momeni, Hamid Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Faculty of Post Graduate Islamic Azad University Southern Unit Tehran Iran Department of Electrical Engineering Tarbiat Modarres University Tehran Iran

ISBN: (纸本)0662478304

Today due to the importance and necessity of implementing security systems in homes and buildings with the capability of higher certainty and lower cost, sensor fusion methods as applicable and high performance methods are attracting the researchers' attention. In this paper, the application of Dempster-Shafer evidential theory and the more general and newer one Dezert-Smarandache theory for implementing a home security system using sensor data fusion have been considered. The benefits of multisensor fusion in comparison with the traditional single sensor systems or systems in which any sensor itself connects to the control unit have been shown.

关键词： Sensor data fusion

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Modulation identification using combined classifiers and co-evolution of classifiers and tests

Modulation identification using combined classifiers and co-...

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International Conference on Information Fusion

作者： M. Mirmomeni B. Moshiri C. Lucas Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

ISBN: (纸本)9780662478300;0662478304

Nowadays, there are considerable attentions to combined classifier. Recently, the focus has been shifting from practical heuristic solutions of combination methods to give a methodological way of design. In this study a co-evolutionary algorithm is presented for this purpose. The algorithm synthesizes an explicit classifier directly from bserved data produced by intelligently generated tests. The algorithm is composed of two co-evolving populations; one population evolves candidate classifiers. The second population evolves informative tests that either extract new information from the pattern or elicit desirable behavior from it The fitness of candidate classifiers is their ability to classify in response to all tests carried out so far; the fitness of candidate tests is their ability to make the classifiers disagree in their classifications. The generality of this modeling-evaluation algorithm is demonstrated by applying the chosen classifier of this algorithm to identify modulation methods and results depict the power of this algorithm.

关键词： Testing Process control Intelligent control Pattern recognition Inference algorithms Evolutionary computation Focusing Design methodology Data mining Power generation

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A recomniender system based on invasive weed optimization algorithm

A recomniender system based on invasive weed optimization al...

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2007 IEEE Congress on Evolutionary Computation, CEC 2007

作者： Rad, Hoda Sepehri Lucas, Caro Robotics and Machine Intelligence Group School of Electrical and Computer Engineering University of Tehran P.O.Box: 11365 - 4563 Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran P.O. Box: 11365- 4563 Tehran Iran School of Cognitive Sciences IPM P.O. Box: 10395 - 5746 Tehran Iran

ISBN: (纸本)1424413400

Recommender systems intend to help users find their interested items from among a large number of items. We continue our previous work that emphasizes on "prioritized user-profile" approach as an effective approach to increase the quality of the recommendations. Prioritized user-profile is an approach that tries to implement more personalized recommendation by assigning different priority importance to each of the features of the user-profile for different users. In order to find the optimal priorities for each user an optimization algorithm is needed. In this paper, we employ a new optimization algorithm namely Invasive Weed Optimization (IWO) for this purpose. IWO is a relatively new and simple algorithm inspired from the invasive habits of growth of weeds in nature. Experimental results showed that IWO achieved the best accuracy in predicting users' interests compared to two other prioritized approaches which were based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) and to standard user-based Pearson algorithm on a movie dataset. © 2007 IEEE.

关键词： Genetic algorithms

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User Modeling for the Result Re-Ranking in the Meta-Search Engines via Reinforcement Learning

User Modeling for the Result Re-Ranking in the Meta-Search E...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Amir Hosein Keyhanipour Behzad Moshiri Caro Lucas Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Department University of Tehran Tehran Iran

Today there are thousands of search engines available, so it is difficult for users to know where they are, how to use them and what topics they best address. Meta-search engines reduce the users' burden by dispatching queries to multiple search engines in parallel and combining the returned results. But there are some problems yet. One of them is that, none of them includes the user model in the answer. In this paper, we propose a mechanism to create a mapping between different categories of users and the underlying search engines using the reinforcement learning approach. By this way, the meta-search engine learns to identify which search engines are most appropriate for particular queries from different user models.

关键词： Metasearch Learning Databases Search engines Information retrieval Intelligent systems Application software Process control Intelligent control Design engineering

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Probabilistic Unit Commitment with Wind Farms Considerations

Probabilistic Unit Commitment with Wind Farms Considerations

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Conference on Power engineering Large engineering Systems (LESCOPE)

作者： Seyed Hamid Hosseini Ehsan Abbasi Member of Center of Excellence in Power System Management and Control Department of Electrical Engineering Sharif University of Technology Tehran Iran

This paper proposes a method for unit commitment in restructured power systems with high penetration of wind farms. As wind is an intermittent source of energy and can not be predicted with high accuracy, reliability of wind farms compare to conventional power plants is lower. By increasing penetration of wind farms in generation system, reliability of power system will decrease. Therefore, reliability constraint should be added to unit commitment (UC) formulation. On the other hand, wind is a green source of energy; additionally environmental crisis is very important issue in the 21 st century. By adding emission constraint to UC, wind energy will be valued. Both reliability and emission constraints are acing as fuzzy constraints. It means that if the UC solution exceeds these constraints limits, that configuration of UC will be penalized by adding augmented cost to total UC cost. To implement these constraints to UC, simulated annealing (SA) has been used because it converges very well under complex and nonlinear constraints. At the end, if any wind farm considered to be off in UC, a must run constraint will make them on and calculate reliability effect of the recommitted wind farm on generation system and decrease from the capacity of the most expensive thermal units equal to the calculated effect of newly committed wind farm on system reliability. Then wind farms that recommitted will be paid 80 percent of the cheapest committed unit in that period. In this way, wind farms will be supported wisely and free power market conditions will be remain unchanged.

关键词： Wind farms Power system reliability Power generation Costs Wind forecasting Accuracy Wind energy generation Wind energy Simulated annealing Power markets

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Using supervised fuzzy clustering and cwt for ventricular late potentials (vlps) detection in high-resolution ecg signal

Using supervised fuzzy clustering and cwt for ventricular la...

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5th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2007

作者： Khorshidi, Gholamreza Salimi Jaafari, Ayyoub Pourmorteza, Amir Motie, Ali Golpayegani, Mohammadreza Hashemi School of Cognitive Sciences Institute for Studies in Theoretical Physics and Mathematics Tehran Iran Faculty of Biomedical Engineering Amirkabir University of Technology Tehran Iran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran Nasrabadi Group of Biomedical Engineering Faculty of Engineering Shahed University Tehran Iran

ISBN: (纸本)9788073683863

Ventricular Late Potentials (VLPs) are lowamplitude, high-frequency components that appear at the end of the QRS complex of a High-Resolution ECG (HRECG) record. VLPs are clinically useful for identifying post-MI (Myocardial Infarction) patients prone to Ventricular Tachycardia (VT) and Sudden Cardiac Death (SCD). In this paper, the Continuous Wavelet Transform (CWT) and a supervised fuzzy clustering algorithm are used together to detect VLP. The terminal part of the QRS complex in the Vector Magnitude (VM) waveform is processed with the CWT to extract a feature vector. Resulting time-frequency representation is subdivided into several sub bands, and the sum of the squared decomposition coefficients is computed in each region. Finally, a supervised Fuzzy clustering method, trained by an appropriate set of these feature vectors, is applied to this data in order to identify VLP.

关键词： Electrocardiograms

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Power management by brain emotional learning algorithm

Power management by brain emotional learning algorithm

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International Conference on ASIC

作者： Mehrzad Samadi Ali Afzali-Kusha Caro Lucas Nanoelectronics Center of Exellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Nowadays having the most energy efficiency is desirable in its own right from both economical and environmental points of view. Dynamic power management is a system level solution for reducing the consumed energy with putting off unused parts of the system and putting them on in an efficient time. The Emotional Learning Algorithm has been introduced to show the effect of emotions as well known stimuli in the quick and almost satisfying decision making in human. The remarkable properties of emotional learning, low computational complexity and fast training, and its simplicity in multi objective problems has made it a powerful methodology in real time control and decision systems, where the gradient based methods and evolutionary algorithms are hard to be used due to their high computational complexity. Recently the emotional approach has been successfully used to obtain multiple objectives in prediction problems of real world phenomena. At first we introduce methods of dynamic power management and then a new method based on BELBIC would be explained. The simulation results show that this method has a high efficiency in various systems.

关键词： Energy management Power system management Computational complexity Energy efficiency Power system economics Power generation economics Economic forecasting Environmental economics Decision making Humans

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Power Management by Brain Emotional Learning Algorithm

Power Management by Brain Emotional Learning Algorithm

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2007 7th International Conference on ASIC Electronic Version(ASICON 2007)

作者： Mehrzad Samadi Ali Afzali-Kusha Caro Lucas Nanoelectronics Center of Exellence School of Electrical and Computer Engineering University of Tehran TehranIran Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran TehranIran

Nowadays having the most energy efficiency is desirable in its own right from both economical and environmental points of *** power management is a system level solution for reducing the consumed energy with putting off unused parts of the system and putting them on in an efficient *** Emotional Learning Algorithm has been introduced to show the effect of emotions as well known stimuli in the quick and almost satisfying decision making in *** remarkable properties of emotional learning,low computational complexity and fast training,and its simplicity in multi objective problems has made it a powerful methodology in real time control and decision systems,where the gradient based methods and evolutionary algorithms are hard to be used due to their high computational *** the emotional approach has been successfully used to obtain multiple objectives in prediction problems of real world *** first we introduce methods of dynamic power management and then a new method based on BELBIC would be *** simulation results show that this method has a high efficiency in various systems.

关键词： Power Management by Brain Emotional Learning Algorithm

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