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Chinese Control Conference (CCC)

作者： Yaojun Liu Xingwen Liu Nyima Tashi Lab. of Complex Systems & Intelligent Control Key Lab. of Electronic Information of State Ethnic Affairs Commission College of Electrical Engineering Southwest Minzu University Chengdu Sichuan China Engineering Research Center for Tibetan Information Processing School of Information Science and Technology Tibet University Lhasa China

Cooperative behavior has been of great concern in evolutionary game researches because of its important role in social life and natural evolution. Since memory can greatly influence the emergence of cooperative behavior, memory-based research on evolutionary games has proliferated in recent years. In the present paper, inspired by the well-known “Stanford marshmallow experiment” (SME), we proposed a multi-memory mechanism in Snowdrift game (SDG) on spatial lattice networks whose core lies in what follows: Players are divided into two groups according to individual self-control; different memory lengths are set by group and by time in a single realization. The simulation results show that our proposed mechanism promotes cooperation level of the considered evolutionary game. More specifically, as memory length increases to an intermediate length, the cooperation level increases as well. For mechanism with short memory length, the effect of population structure is obvious and small values of adjusting factor can intensively facilitate high-frequency cooperative behavior. These findings may be helpful to understand the connection between population heterogeneity and the emergence of high cooperation.

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An associative memory system for incremental learning and temporal sequence

An associative memory system for incremental learning and te...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Shen, Furao Yu, Hui Kasai, Wataru Hasegawa, Osamu State Key Laboratory for Novel Software Technology Jiangyin Information Technology Research Institute Nanjing University Nanjing 210093 China Department of Computer Intelligence and Systems Science Tokyo Institute of Technology Yokohama 226-8503 Japan Imaging Science and Engineering Lab. Tokyo Institute of Technology R2-52 4259 Nagatsuda Midori-ku Yokohama 226-8503 Japan

ISBN: (纸本)9781424469178

An associative memory (AM) system is proposed to realize incremental learning and temporal sequence learning. The proposed system is constructed with three layer networks: The input layer inputs key vectors, response vectors, and the associative relation between vectors. The memory layer stores input vectors incrementally to corresponding classes. The associative layer builds associative relations between classes. The proposed method can incrementally learn key vectors and response vectors;store and recall both static information and temporal sequence information;and recall information from incomplete or noise-polluted inputs. Experiments using binary data, real-value data, and temporal sequences show that the proposed method works well. © 2010 IEEE.

关键词： Vectors

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Real-Time Estimation for the Swimming Direction of Robotic Fish Based on IMU Sensors*

Real-Time Estimation for the Swimming Direction of Robotic F...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Shikun Li Yufan Zhai Chen Wang Guangming Xie State Key Laboratory for Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China Institute of Ocean Research Peking University Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

An increasing number of underwater robots inspired by Carangidae are developed, which is characterized by high efficiency and flexibility. However, estimating the swimming direction of these robotic fish is challenging due to the constant swinging of the head during movement, which complicates precise control. In this study, we installed two low-cost inertial measurement unit (IMU) sensors separately on the head and tail parts of a double-joint robotic fish and presented a method for accurately and timely estimating the swimming direction. Firstly, we effectively compensated for the yaw angle drift of the IMU sensors through a fused Kalman Filter. Furthermore, we propose the Anti-Shake Estimation (ASE) algorithm to calculate the real-time swimming direction using filtered yaw angles at a high updating rate of 100Hz. Finally, we applied the method to swimming direction feedback control for evaluation and comparison. The results show that our ASE method performs better than other existing methods in straight-line swimming experiments. The experiment of S-curve swimming also demonstrates the effectiveness of our method in complex missions.

关键词： Measurement units Estimation Tail Sensor phenomena and characterization Sensor fusion Robot sensing systems Fish

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Decentralized circle formation control for fish-like robots in the real-world via reinforcement learning

arXiv

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arXiv 2021年

作者： Zhang, Tianhao Li, Yueheng Li, Shuai Ye, Qiwei Wang, Chen Xie, Guangming The State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China Microsoft Research Asia Beijing100871 China National Engineering Research Center of Software Engineering Peking University Beijing100871 China

In this paper, the circle formation control problem is addressed for a group of cooperative underactuated fish-like robots involving unknown nonlinear dynamics and disturbances. Based on the reinforcement learning and cognitive consistency theory, we propose a decentralized controller without the knowledge of the dynamics of the fish-like robots. The proposed controller can be transferred from simulation to reality. It is only trained in our established simulation environment, and the trained controller can be deployed to real robots without any manual tuning. Simulation results confirm that the proposed model-free robust formation control method is scalab.e with respect to the group size of the robots and outperforms other representative RL algorithms. Several experiments in the real world verify the effectiveness of our RL-based approach for circle formation *** Codes 68T40 © 2021, CC BY.

关键词： Reinforcement learning

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Sparse signal analysis using Ramanujan sums

Sparse signal analysis using Ramanujan sums

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Chen, Guangyi Krishnan, Sridhar Liu, Weihua Xie, Wenfang Department of Computer Science and Software Engineering Concordia University Montreal QC H3G 1M8 Canada Department of Computer and Electrical Engineering Ryerson University Toronto ON Canada State Key Lab. of Virtual Reality Technology and Systems Beihang University No 37 Xueyuan Rd. Haidian District 100191 Beijing China Department of Mechanical and Industrial Engineering Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9783642394812

In this paper, we perform sparse signal analysis by using the Ramanujan Sums (RS). The RS are orthogonal in nature and therefore offer excellent energy conservation. Our analysis shows that the RS can compress the energy of a periodic impulse chain signal into fewer number of RS coefficients than the Fourier transform (FT). In addition, the RS are faster than the FT in computation time because we can calculate the RS basis functions only once and save them to a file. We can retrieve these RS basis functions for our calculation instead of computing them online. To process a signal of 128 samples, we spend 1.0 millisecond for the RS and 5.82 milliseconds for the FT by using our unoptimized Matlab.code. © 2013 Springer-Verlag.

关键词： Signal analysis

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Energy-aware loop parallelism maximization for multi-core DSP architectures

Energy-aware loop parallelism maximization for multi-core DS...

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2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010

作者： Qiu, Meikang Niu, Jian-Wei Yang, Laurence T. Qin, Xiao Zhang, Senlin Wang, Bin Department of Electrical and Computer Engineering University of Kentucky Lexington KY 40506 United States State Key Lab. of Software Develop. Environment Beihang University Beijing 100191 China Department of Computer Science St. Francis Xavier University Antigonish NS B2G 2W5 Canada Dept. of Computer Science and Software Engineering Auburn University Auburn AL 36849 United States Dept. of Systems Science and Engineering Zhejiang University Hangzhou 310027 China Dept. of Computer Science and Engineering Wright State University Dayton OH 45435 United States

ISBN: (纸本)9780769543314

With the advance of semiconductor, multi-core architecture is inevitable in today's embedded system design. Nested loops are usually the most critical part in multimedia and high performance DSP (Digital Signal Processing) systems. Hence, maximizing loop parallelism is an important issue to improve the performance of a modern compiler. This paper studies how to maximize the system performance with the consideration of energy reduction for applications with multidimensional nested loops on multi-core DSP architectures. An algorithm, EALPM (Energy-Aware Loop Parallelism Maximization), is proposed in this paper. We implemented a two phase strategy. First, the strategy uses retiming and loop transformation to parallelize nested loops. Then the strategy employs a novel voltage assignment algorithm to reduce total energy consumption. The experimental results show that on average, both performance and energy-saving can be significantly improved using the EALPM algorithm. © 2010 IEEE.

关键词： Digital signal processing

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A Review of Artificial Fish Swarm Algorithms: Recent Advances and Applications

arXiv

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arXiv 2020年

作者： Pourpanah, Farhad Wang, Ran Lim, Chee Peng Wang, Xi-Zhao Yazdani, Danial College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China Department of Electrical and Computer Engineering University of Windsor Canada College of Mathematics and Statistics Shenzhen Key Lab. of Advanced Machine Learning and Applications Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China Institute for Intelligent Systems Research and Innovation Deakin University Australia College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China School of Computer Science and Engineering Southern University of Science and Technology China

The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological behaviors of fish schooling in nature, viz., the preying, swarming and following behaviors. Owing to a number of salient properties, which include flexibility, fast convergence, and insensitivity to the initial parameter settings, the family of AFSA has emerged as an effective Swarm Intelligence (SI) methodology that has been widely applied to solve real-world optimization problems. Since its introduction in 2002, many improved and hybrid AFSA models have been developed to tackle continuous, binary, and combinatorial optimization problems. This paper aims to present a concise review of the continuous AFSA, encompassing the original ASFA, its improvements and hybrid models, as well as their associated applications. We focus on articles published in high-quality journals since 2013. Our review provides insights into AFSA parameters modifications, procedure and sub-functions. The main reasons for these enhancements and the comparison results with other hybrid methods are discussed. In addition, hybrid, multi-objective and dynamic AFSA models that have been proposed to solve continuous optimization problems are elucidated. We also analyse possible AFSA enhancements and highlight future research directions for advancing AFSA-based models. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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PPSS: A Privacy-Preserving Supervision Scheme Based on Blockchain

PPSS: A Privacy-Preserving Supervision Scheme Based on Block...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Ming Chen Peichang Shi Xiang Fu Feng Jiang Fei Gao Penghui Ma Jinzhu Kong National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha China Kylin Software Co.LTD Changsha China Zhejiang Lab Hangzhou China

In JointCloud Computing, multi-party participation introduces complexity and uncertainty. For all participants in JointCloud Computing, both continuous supervision and necessary privacy protection are required. Traditional supervision methods usually adopt the centralized information interaction mode, which has such defects as collusion of interests, single point of failure, privacy disclosure, etc. Building a decentralized supervision mechanism has become a new research direction. In this paper, we propose PPSS, a privacy-preserving supervision scheme based on blockchain, which decentralizes the supervision of the participants in JointCloud Computing, and combines the “double encryptions” and “threshold encryption” technologies to provide privacy protection. While making full use of the decentralization of the blockchain, a committee is established to carry out the analysis and decision-making tasks in terms of supervision and privacy protection. Experimental results indicate that PPSS can balance performance and security by reasonably configuring the committee.

关键词： Privacy Uncertainty Decision making Buildings Reliability engineering Blockchains complexity theory

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General formation control for multi-agent systems with double-integrator dynamics

arXiv

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arXiv 2018年

作者： Wang, Chen Xia, Weiguo Sun, Jinan Fan, Ruifeng Xie, Guangming State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China

We study the general formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations that the distances between neighboring agents or the distances from each agent to the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors. A distributed control law is designed using the limit-cycle based idea to solve the problem. One merit of the controller is that it can be implemented by each agent in its Frenet-Serret frame so that only local information is utilized without knowing global information. Theoretical analysis is provided of the equilibrium of the N-agent system and of the convergence of its converging part. Numerical simulations are given to show the effectiveness and performance of the proposed controller. Copyright © 2018, The Authors. All rights reserved.

关键词： Mobile agents

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HeROS: A simulation platform for heterogeneous robotic swarms

HeROS: A simulation platform for heterogeneous robotic swarm...

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第三十八届中国控制会议

作者： Shuai Li Yuanfang Wan Pengzhou He Chen Wang Jinan Sun Yanling Zhang Xuyang Li Guangming Xie The State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University School of Automation and Electrical Engineering University of Science and Technology Beijing National Engineering Research Center for Software Engineering Peking University Xi'an Bibang Intelligent Technology Co. Ltd.

This paper presents HeROS, which is a novel simulation platform for heterogeneous robotic swarms. Compared with some existing simulation platforms, our HeROS(Heterogeneous Robotic Swarms Simulation) platform is more efficient due to its special designed communication methods and framework. Besides, it's convenient for use since we provide many kinds of control functions with free API's. It also supports many external libraries, which can be used to develop different simulation tasks. Using our developed platform, a mission of target search and tracking is realized as a case study, where a UAV-UGV heterogeneous system consisting of a UAV and two UGVs is required to search for a ground target and then move close to *** implementation of the task successfully shows the effectiveness and performance of the HeROS platform.

关键词： Heterogeneous robotic swarms simulation platform UAV UGV cooperation

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