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Spectrum Sharing and Consensus Performance of Vehicular Networks based on Deep Multi-User Reinforcement Learning

Spectrum Sharing and Consensus Performance of Vehicular Netw...

引用

ieee International symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Muhammad Muzamil Aslam Ali Tufail Zahoor Ahmed Kassim Kalinaki Muhammad Nasir Rosyzie Anna Awg Haji Mohd Apong School of Digital Science Universiti Brunei Darussalam Brunei Department of Automation Shanghai Jiaotong University Shanghai China

The idea of an agent is useful for describing circumstances in which it is difficult or perhaps impossible for a single entity to gain all the necessary knowledge about the state of a system. The multiagent system is known to be useful in designing distributed solutions. control action, data, or even both are distributed. In this research, we investigate the performance of vehicular networks based on deep multi-user reinforcement learning, where numerous V2V links use the already occupied V2I frequency spectrum, in terms of spectrum sharing and consensus. Goal is a multiuser strategy for reaching the spectrum that enhances network distributed behavior without any contact or message communication. Due to the large number of vehicles and to overcome the problem, we developed consensus and spectrum sharing algorithms based on deep multi-user reinforcement learning.

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Discrete event simulation approach for evaluation and estimation of various production parameters 20

Discrete event simulation approach for evaluation and estima...

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20th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Kumar, Rahul Budinska, Ivana Balogh, Zoltan Gatial, Emil Matejka, Tomas Slovak Acad Sci Inst Informat Bratislava Slovakia MAT Obaly Sro Prievidza Slovakia

ISBN: (纸本)9781728183398

In this research we focus on minimizing the makespan, number of reconfiguration and wastage of materials due to reconfigurations for a set of non identical parallel machines. A mathematical model of the scheduling problem is explained, subjected to various production related constraints and is optimized using a heuristic approach. Optimality of the schedule generated is tested on a simulation platform created as close to real production system, modelling all the important uncertainty in the process. Simulation model also estimates the real order completion time and total wastage in the production process. A real manufacturing process of plastic foil bags is used in the case study to find and test the proposed solution. This approach acts effective in planning and scheduling of orders in small and medium scale industries as the approach is data driven.

关键词： Heuristic algorithm Schedule optimization Production planning and control Discrete event simulation

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Problems of Gait Analysis in Medical cases 20

Problems of Gait Analysis in Medical cases

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20th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Komoroczki, Henriette Steiner Fekete, Gyorgy Lovas, Robert Kertesz, Zsolt Kaszala, Klaudia Abonyi, Barbara Obuda Univ John von Neumann Fac Informat Inst Cyber Phys Syst Budapest Hungary Obuda Univ John von Neumann Fac Informat AIAIMDI Sch PhD Studies Inst Cyber Phys Syst Budapest Hungary Budapest Univ Technol & Econ Dept Control Engn & Informat Technol Budapest Hungary Univ Phys Educ Inst Hlth Sci & Sports Med Sch PhD Studies Budapest Hungary Univ Phys Educ Sch PhD Studies Sport Sci Budapest Hungary

ISBN: (纸本)9781728183398

Motion capture is a special the process of recording live motion events.. We look for differences between the three measuring systems and present a few results from our laboratory. These results justify the application of motion capture. Our laboratory uses this method for diagnosis and to test therapeutic methods for various motor dysfunctions. We analyzed 7733 cases.

关键词： Motion capture Vicon Medtronic Rheumatoid arthritis visually impaired

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PSO-assisted Lyapunov control design for quantum systems

PSO-assisted Lyapunov control design for quantum systems

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Guan, Xiaoke Kuang, Sen Dong, Daoyi Univ Sci & Technol China Dept Automat Hefei 230027 Anhui Peoples R China Univ New South Wales Sch Engn & Informat Technol Canberra ACT 2600 Australia

ISBN: (纸本)9781728125473

By using a quadratic Lyapunov function with unknown parameters and a particle swarm optimization (PSO) algorithm, this paper proposes a new Lyapunov control scheme for quantum systems. This approach can achieve high-probability population transfer to a given target state. For the case when the target state is an eigenstate of the internal Hamiltonian, we introduce a virtual control law into the system model and design corresponding control law. The stability of the system under the action of the Lyapunov control law is analyzed via the LaSalle invariance principle. For the case when the target state is a superposition state, we design a control law by performing a unitary transformation for the quantum system model under consideration. To achieve desired stale transfer, we further introduce a PSO algorithm to search for the unknown parameters contained in the control law. Numerical results on a five-level quantum system and a three-qubit system are presented to demonstrate the effectiveness of the proposed approaches.

关键词： Quantum systems Lyapunov control particle swarm optimization quantum control

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Vibration Characteristics of Plate Structure Based on Simulation System 13

Vibration Characteristics of Plate Structure Based on Simula...

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13th International symposium on computational intelligence and Design (ISCID)

作者： Zhao, Minghui Chen, Qijun Zhang, Shihong Tongji Univ Sch Elect & Informat Engn Dept Control Sci & Engn Shanghai Peoples R China China Coal Technol & Engn Grp Shanghai Co Ltd Shanghai Peoples R China

ISBN: (纸本)9781728184463

Taking the vibration acoustics analysis of a circular plate as an example, after using ABAQUS, Python and MATLAB software to realize the virtual experiment simulation system based on finite element analysis, computer simulation and data processing, the rules of the size and structure of circular plate, material parameters, external force load and the frequency of sound pressure vibration caused by the vibration of circular plate are analyzed.

关键词： Virtual experiment Vibration acoustics Finite element analysis Rules

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Proximal Policy Optimization with Continuous Bounded Action Space via the Beta Distribution

Proximal Policy Optimization with Continuous Bounded Action ...

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ieee symposium Series on computational intelligence (SSCI)

作者： Irving G. B. Petrazzini Eric A. Antonelo Automation and Systems Engineering Federal University of Santa Catarina Florianópolis Santa Catarina

ISBN: (纸本)9781728190495

Reinforcement learning methods for continuous control tasks have evolved in recent years generating a family of policy gradient methods that rely primarily on a Gaussian distribution for modeling a stochastic policy. However, the Gaussian distribution has an infinite support, whereas real world applications usually have a bounded action space. This dissonance causes an estimation bias that can be eliminated if the Beta distribution is used for the policy instead, as it presents a finite support. In this work, we investigate how this Beta policy performs when it is trained by the Proximal Policy Optimization (PPO) algorithm on two continuous control tasks from OpenAI gym. For both tasks, the Beta policy is superior to the Gaussian policy in terms of agent's final expected reward, also showing more stability and faster convergence of the training process. For the CarRacing environment with high-dimensional image input, the agent's success rate was improved by 63% over the Gaussian policy.

关键词： Training Stochastic processes Estimation Reinforcement learning Aerospace electronics Gaussian distribution Task analysis

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Quantifying cooperation between artificial agents using synergistic information

Quantifying cooperation between artificial agents using syne...

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ieee symposium Series on computational intelligence (SSCI)

作者： Patricia Wollstadt Matti Krüger Honda Research Institute Europe GmbH Offenbach/Main Germany

ISBN: (纸本)9781665487696

When designing interactive human-machine sys-tems, it is often assumed that it is desirable for such systems to behave cooperatively towards a human operator in order to improve trust, acceptance, and usability, but also to increase task efficiency. To design cooperative human-machine interaction (HMI) systems, we have to be able to define and quantitatively describe cooperative behavior, for example, to control, optimize, or evaluate the interaction. Despite the increased interest in cooperative HMI in recent years, an approach that provides a suitable definition of cooperation and also a method for its quantification is still missing. In the present work, we therefore develop a novel definition of cooperative behavior in HMI contexts, based on which we propose to quantify cooperation using recent methods from information theory. We define cooperation as joint, coordinated actions that are mutually adapted such as to facilitate the realization of a goal. Thus, cooperation is characterized by a synergistic effect of joint actions towards the goal. Here, we propose to quantify cooperation using the recently introduced partial information decomposition framework from information theory, which proposes measures to quantify the synergistic contributions of two inputs to a target variable. In particular, we propose to apply the synergy measure to two or more input variables describing agents' actions towards a target variable that describes the current goal state. As a first validation, we applied our approach in a grid-world environment, in which two agents solve a cooperative foraging task. We found that synergy was higher for agents implementing cooperative strategies compared to baseline and non-cooperative strategies, and we found higher synergy in trials with high numbers of cooperative actions. We conclude that the synergy is a promising candidate measure for identifying cooperative behavior in goal-oriented interactions.

关键词： Atmospheric measurements Current measurement computational modeling Games Particle measurements Behavioral sciences Reliability

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Nonlinear Model Predictive control of Industrial Grinding Circuits using Machine Learning

Nonlinear Model Predictive Control of Industrial Grinding Ci...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Inapakurthi, Ravi Kiran Miriyala, Srinivas Soumitri Kolluri, Suryanarayana Mitra, Kishalay Indian Inst Technol Dept Chem Engn Hyderabad India Univ Texas Austin Walker Dept Mech Engn & Mat Sci Engn Austin TX 78712 USA

ISBN: (纸本)9781728125473

control problems of engineering interest such as industrial grinding circuit (IGC) are essential for minimizing the energy consumption, maximizing throughput or maintaining product quality to make these processes energy sustainable in future. Detailed physics based models, although provide more insight into the process and yield accurate results, often cannot be used for control purposes owing to the high computational time involved in solving the complicated mass, momentum, energy balance equations used to describe the process. In the current study, the aim is to use optimally designed Recurrent Neural Networks, a type of data-based modeling technique popularly used in the machine learning domain, for modeling transients involved in the IGC and test its effectiveness in set point (SP) tracking under the nonlinear model predictive control (NMPC) framework. SP tracking of throughput (related to the amount of raw materials processed to give products) and recirculation load (related to the energy consumption) is performed. We observe that the developed machine learning based models could effectively perform the SP tracking for nonlinear industrial process like grinding.

关键词： model predictive control optimization data based models process system engineering

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Teaching of Machinery Manufacturing Specialty Courses under the Background of Artificial intelligence

Teaching of Machinery Manufacturing Specialty Courses under ...

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2021 International symposium on Advances in Informatics, Electronics and Education, ISAIEE 2021

作者： Liu, Honghua Cao, Shen Tan, Wenping Gong, Jingzhong Hunan International Economics University College of Information and Mechatronical Engineering Hunan Changsha410205 China

ISBN: (纸本)9781665478748

Artificial intelligence(AI) is a subject centered on computer technology and involves dozens of disciplines, including mechanical manufacturing automation, automatic control, etc. With the continuous development of Internet technology and computer network communications and other scientific and technological fields, AI has been widely used in various industries. Because professional teachers focus on imparting professional knowledge and students focus on professional learning, they ignore ideological education, and some improper speech or behavior errors occur. Therefore, based on the improvement of the ideological level of students majoring in machine manufacturing, this article proposes to study the addition of ideological and political education(IPE) to the teaching of mechanical manufacturing in the AI environment. This article mainly uses the investigation method and data analysis method to conduct an in-depth analysis of the IPE of AI in professional courses, and finally obtain the results through the investigation. The survey shows that 66% of people still agree with the use of AI to learn majors and improve their ideological quality. Therefore, college teachers can try to use AI to teach ideological and politica(IP)I courses. © 2021 ieee.

关键词： Teaching

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Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving

Space, Time, and Interaction: A Taxonomy of Corner Cases in ...

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ieee symposium Series on computational intelligence (SSCI)

作者： Kevin Rösch Florian Heidecker Julian Truetsch Kamil Kowol Clemens Schicktanz Maarten Bieshaare Bernhard Sick Christoph Stiller Mobile Perception Systems FZI Research Center for Information Technology Karlsruhe Germany Intelligent Embedded Systems University of Kassel Kassel Germany School of Mathematics and Natural Sciences University of Wuppertal Wuppertal Germany German Aerospace Center (DLR) Institute of Transportation Systems Berlin Germany Robert Bosch GmbH Hildesheim Germany Institute of Measurement and Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9781665487696

Trajectory data analysis is an essential component for highly automated driving. Complex models developed with these data predict other road users' movement and behavior patterns. Based on these predictions - and additional contextual information such as the course of the road, (traffic) rules, and interaction with other road users - the highly automated vehicle (HAV) must be able to reliably and safely perform the task assigned to it, e.g., moving from point A to B. Ideally, the HAV moves safely through its environment, just as we would expect a human driver to do. However, if unusual trajectories occur, so-called trajectory corner cases, a human driver can usually cope well, but an HAV can quickly get into trouble. In the definition of trajectory corner cases, which we provide in this work, we will consider the relevance of unusual trajectories with respect to the task at hand. Based on this, we will also present a taxonomy of different trajectory corner cases. The categorization of corner cases into the taxonomy will be shown with examples and is done by cause and required data sources. To illustrate the complexity between the machine learning (ML) model and the corner case cause, we present a general processing chain underlying the taxonomy.

关键词： Roads Soft sensors Taxonomy Predictive models Data models Trajectory Reliability

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