Resource Type

Journal Article 727

Year

2024 3

2023 88

2022 96

2021 90

2020 71

2019 63

2018 66

2017 41

2016 23

2015 24

2014 11

2013 6

2012 12

2011 9

2010 7

2009 3

2008 10

2007 9

2006 20

2005 12

open ︾

Keywords

Artificial intelligence 35

intelligent manufacturing 20

Machine learning 18

artificial intelligence 18

Deep learning 11

Intelligent manufacturing 8

Multi-agent system 8

Multi-agent systems 6

industrial software 6

Smart manufacturing 5

intelligence 5

Additive manufacturing 4

Process industry 4

Reinforcement learning 4

Big data 3

Industry 4.0 3

artificial intelligence (AI) 3

3D printing 2

4D printing 2

open ︾

Search scope:

排序： Display mode:

The Application of Multi-agent Based Distributed Intelligent Control in VAV Air Conditioning System

Zhang Hongwei,Wu Aiguo,Sheng Tao

Strategic Study of CAE 2006, Volume 8, Issue 7,   Pages 58-62

Abstract:

A VAV system can be treated as a multi-agent system. In this paper, a multi-agent-based distributed intelligent control method is presented to solve the problem of concordance and decoupling in the VAV system. A simulation program of VAV system is set up for control analysis. Through a simulation, this control method has been proved to be satisfactory.

Keywords： VAV     agent     multi-agent system     distributed intelligent control    

HTML PDF Collect

Coach-assisted multi-agent reinforcement learning framework for unexpected crashed agents Research Article

Jian ZHAO, Youpeng ZHAO, Weixun WANG, Mingyu YANG, Xunhan HU, Wengang ZHOU, Jianye HAO, Houqiang LI

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1032-1042 doi: 10.1631/FITEE.2100594

Abstract: Multi-agent is difficult to apply in practice, partially because of the gap between simulated and real-world scenarios. One reason for the gap is that simulated systems always assume that agents can work normally all the time, while in practice, one or more agents may unexpectedly "crash" during the coordination process due to inevitable hardware or software failures. Such crashes destroy the cooperation among agents and lead to performance degradation. In this work, we present a formal conceptualization of a cooperative multi-agent system with unexpected crashes. To enhance the robustness of the system to crashes, we propose a coach-assisted multi-agent framework that introduces a virtual coach agent to adjust the crash rate during training. We have designed three coaching strategies (fixed crash rate, curriculum learning, and adaptive crash rate) and a re-sampling strategy for our coach agent. To our knowledge, this work is the first to study unexpected crashes in a . Extensive experiments on grid-world and StarCraft II micromanagement tasks demonstrate the efficacy of the adaptive strategy compared with the fixed crash rate strategy and curriculum learning strategy. The ablation study further illustrates the effectiveness of our re-sampling strategy.

Keywords： Multi-agent system     Reinforcement learning     Unexpected crashed agents    

HTML PDF Collect

Prospects for multi-agent collaboration and gaming: challenge, technology, and application Perspective

Yu LIU, Zhi LI, Zhizhuo JIANG, You HE

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1002-1009 doi: 10.1631/FITEE.2200055

Abstract: Recent years have witnessed significant improvement of multi-agent systems for solving various decision-making problems in complex environments and achievement of similar or even better performance than humans. In this study, we briefly review multi-agent collaboration and gaming technology from three perspectives, i.e., task challenges, technology directions, and application areas. We first highlight the typical research problems and challenges in the recent work on multi-agent systems. Then we discuss some of the promising research directions on multi-agent collaboration and gaming tasks. Finally, we provide some focused prospects on the application areas in this field.

Keywords： 多智能体；博弈论；集体智能；强化学习；智能控制    

HTML PDF Collect

Existence and practice of gaming: thoughts on the development of multi-agent system gaming Perspective

Qi DONG, Zhenyu WU, Jun LU, Fengsong SUN, Jinyu WANG, Yanyu YANG, Xiaozhou SHANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 995-1001 doi: 10.1631/FITEE.2100593

Abstract: Game is a universal being in the universe. Starting with human understanding of the game process, we discuss the existence and practice of gaming, expound challenges in multi-agent gaming, and put forward a theoretical framework for a multiagent evolutionary game based on the idea of evolution and system theory. Taking the next-generation early warning and detection system as an example, we introduce the applications of multi-agent evolutionary game. We construct a multi-agent selforganizing game decision-making model and develop a multi-agent method based on reinforcement learning, which are significant in studying organized and systematic game behaviors in a high-dimensional complex environment.

Keywords： 博弈；多智能体系统；多智能体演化博弈；预警探测    

HTML PDF Collect

Decentralized multi-agent reinforcement learning with networked agents: recent advances Review Article

Kaiqing Zhang, Zhuoran Yang, Tamer Başar,kzhang66@illinois.edu,zy6@princeton.edu,basar1@illinois.edu

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 802-814 doi: 10.1631/FITEE.1900661

Abstract: Multi-agent (MARL) has long been a significant research topic in both machine learning and control systems. Recent development of (single-agent) deep has created a resurgence of interest in developing new MARL algorithms, especially those founded on theoretical analysis. In this paper, we review recent advances on a sub-area of this topic: decentralized MARL with networked agents. In this scenario, multiple agents perform sequential decision-making in a common environment, and without the coordination of any central controller, while being allowed to exchange information with their neighbors over a communication network. Such a setting finds broad applications in the control and operation of robots, unmanned vehicles, mobile sensor networks, and the smart grid. This review covers several of our research endeavors in this direction, as well as progress made by other researchers along the line. We hope that this review promotes additional research efforts in this exciting yet challenging area.

Keywords： 强化学习；多智能体系统；网络系统；一致性优化；分布式优化；博弈论    

HTML PDF Collect

A multi-agent architecture for scheduling in platform-based smart manufacturing systems Special Feature on Industrial Internet

Yong-kui Liu, Xue-song Zhang, Lin Zhang, Fei Tao, Li-hui Wang,yongkuiliu@163.com,xs_zhang@126.com,zhanglin@buaa.edu.cn,ftao@buaa.edu.cn,lihuiw@kth.se

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 11,   Pages 1465-1492 doi: 10.1631/FITEE.1900094

Abstract: During the past years, a number of concepts have been proposed, such as cloud manufacturing, Industry 4.0, and Industrial Internet. One of their common aims is to optimize the collaborative resource configuration across enterprises by establishing s that aggregate distributed resources. In all of these concepts, a complete manufacturing system consists of distributed physical manufacturing systems and a containing the virtual manufacturing systems mapped from the physical ones. We call such manufacturing systems -based systems (PSMSs). A PSMS can therefore be regarded as a huge cyber-physical system with the cyber part being the and the physical part being the corresponding physical manufacturing system. A significant issue for a PSMS is how to optimally schedule the aggregated resources. technology provides an effective approach for solving this issue. In this paper we propose a architecture for in PSMSs, which consists of a -level system (MAS) and an enterprise- level MAS. Procedures, characteristics, and requirements of in PSMSs are presented. A model for in a PSMS based on the architecture is proposed. A case study is conducted to demonstrate the effectiveness of the proposed architecture and model.

Keywords： 平台；智能制造；多智能体；调度    

HTML PDF Collect

Designing a novel consensus protocol formultiagent systemswith general dynamics under directed networks Article

Hao-liang LI, Ren-nong YANG, Qiu-ni LI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1071-1081 doi: 10.1631/FITEE.1601422

Abstract: The consensus problem for general linear multi-agent systems (MASs) under directed topology is investigated. First, a novel consensus protocol based on proportional-integral-derivative (PID) control is proposed. Second, the consensus problem is converted into an asymptotic stability problem through transformations. Third, through a state projection method the consensus condition is proved and the explicit expression of the consensus function is given. Then, a Lyapunov function is constructed and the gain matrices of the protocol are given based on the linear matrix inequality. Finally, two experiments are conducted to explain the advantages of the method. Simulation results show the effectiveness of the proposed algorithm.

Keywords： Multi-agent     Consensus     PID control     Linear matrix inequality    

HTML PDF Collect

The Mechanics of 3D Multi-body Contact System of Long Shell and Tyres

Liang Xiaoling,Xiao Yougang,Li Xuejun

Strategic Study of CAE 2005, Volume 7, Issue 12,   Pages 41-44

Abstract:

According to the high iterative feature of shell and tyre structure, the multi-level substructure technique is adopted to set up the multi-body contact model between tyres and long shell. Applying parametric quadratic programming method, the multi-body contact FEM analysis of the No.2 rotary kiln in Henan Branch of China Aluminum Company is done, and the conclusions are as follows： The equivalent stress of shell at supports changes 5 times, and at other parts changes 4 times; the strength of shell at supports is weak, and at other parts is affluent; the strength of shell at the supports 2 and 3 is the weakest.

Keywords： shell     multi-body contact     multi-level substructure     mechanical property    

HTML PDF Collect

Dynamic grouping of heterogeneous agents for exploration and strike missions Research Article

Chen CHEN, Xiaochen WU, Jie CHEN, Panos M. PARDALOS, Shuxin DING,xiaofan@bit.edu.cn,wsygdhrwxc@sina.com,pardalos@ufl.edu

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 1,   Pages 86-100 doi: 10.1631/FITEE.2000352

Abstract: The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat agents. This study aims to address the problem of dynamic construction of mission groups under new requirements. Agents are heterogeneous, and a method must dynamically form new groups in circumstances where missions are constantly being explored. In our method, a strategy that combines s and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new missions. The degree of matching between the mission requirements and the group's capabilities, and the communication cost of are used as indicators to evaluate the quality of the group. The response threshold method and the ant colony algorithm are selected as the comparison algorithms in the simulations. The results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.

Keywords： Multi-agent     Dynamic missions     Group formation     Heuristic rule     Networking overhead    

HTML PDF Collect

Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments Research

Yan Shao, Zhi-feng Zhao, Rong-peng Li, Yu-geng Zhou,shaoy@zju.edu.cn,zhaozf@zhejianglab.com,lirongpeng@zju.edu.cn,yugeng.zhou@wfjyjt.com

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 5,   Pages 649-808 doi: 10.1631/FITEE.1900659

Abstract: Coordinating multiple unmanned aerial vehicles (multi-UAVs) is a challenging technique in highly dynamic and sophisticated environments. Based on as well as current mainstream unmanned system controlling algorithms, we propose a strategy for multi-UAVs to acquire targets with limited prior knowledge. In particular, we put forward a more reasonable and effective pheromone update mechanism, by improving digital pheromone fusion algorithms for different semantic pheromones and planning individuals’ probabilistic behavioral decision-making schemes. Also, inspired by the flocking model in nature, considering the limitations of some individuals in perception and communication, we design a model on top of Olfati-Saber’s algorithm for flocking control, by further replacing the pheromone scalar to a vector. Simulation results show that the proposed algorithm can yield superior performance in terms of coverage, detection and revisit efficiency, and the capability of obstacle avoidance.

Keywords： 群体智能；数字信息素；人工势场；领航算法    

HTML PDF Collect

Stability of General Linear Dynamic Multi-Agent Systems under Switching Topologies with Positive Real Eigenvalues Article

Shengbo Eben Li, Zhitao Wang, Yang Zheng, Diange Yang, Keyou You

Engineering 2020, Volume 6, Issue 6,   Pages 688-694 doi: 10.1016/j.eng.2020.05.006

Abstract:

The time-varying network topology can significantly affect the stability of multi-agent systems. This paper examines the stability of leader–follower multi-agent systems with general linear dynamics and switching network topologies, which have applications in the platooning of connected vehicles. The switching interaction topology is modeled as a class of directed graphs in order to describe the information exchange between multi-agent systems, where the eigenvalues of every associated matrix are required to be positive real. The Hurwitz criterion and the Riccati inequality are used to design a distributed control law and estimate the convergence speed of the closed-loop system. A sufficient condition is provided for the stability of multi-agent systems under switching topologies. A common Lyapunov function is formulated to prove closed-loop stability for the directed network with switching topologies. The result is applied to a typical cyber–physical system—that is, a connected vehicle platoon—which illustrates the effectiveness of the proposed method.

Keywords： Stability     Multi-agent system     Switching topologies     Common Lyapunov function    

HTML PDF Collect

Multi-agent differential game based cooperative synchronization control using a data-driven method Research Article

Yu SHI, Yongzhao HUA, Jianglong YU, Xiwang DONG, Zhang REN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1043-1056 doi: 10.1631/FITEE.2200001

Abstract: This paper studies the multi-agent based problem and its application to cooperative . A systematized formulation and analysis method for the multi-agent is proposed and a methodology based on the (RL) technique is given. First, it is pointed out that typical distributed controllers may not necessarily lead to global Nash equilibrium of the in general cases because of the coupling of networked interactions. Second, to this end, an alternative local Nash solution is derived by defining the best response concept, while the problem is decomposed into local s. An off-policy RL algorithm using neighboring interactive data is constructed to update the controller without requiring a system model, while the stability and robustness properties are proved. Third, to further tackle the dilemma, another configuration is investigated based on modified coupling index functions. The distributed solution can achieve global Nash equilibrium in contrast to the previous case while guaranteeing the stability. An equivalent parallel RL method is constructed corresponding to this Nash solution. Finally, the effectiveness of the learning process and the stability of are illustrated in simulation results.

Keywords： Multi-agent system     Differential game     Synchronization control     Data-driven     Reinforcement learning    

HTML PDF Collect

Multi-agent deep reinforcement learning for end–edge orchestrated resource allocation in industrial wireless networks Research Article

Xiaoyu LIU, Chi XU, Haibin YU, Peng ZENG,liuxiaoyu1@sia.cn,xuchi@sia.cn,yhb@sia.cn,zp@sia.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 1,   Pages 47-60 doi: 10.1631/FITEE.2100331

Abstract: Edge artificial intelligence will empower the ever simple (IWNs) supporting complex and dynamic tasks by collaboratively exploiting the computation and communication resources of both machine-type devices (MTDs) and edge servers. In this paper, we propose a based resource allocation (MADRL-RA) algorithm for IWNs to support computation-intensive and -sensitive applications. First, we present the system model of IWNs, wherein each MTD is regarded as a self-learning agent. Then, we apply the Markov decision process to formulate a minimum system overhead problem with joint optimization of and . Next, we employ MADRL to defeat the explosive state space and learn an effective resource allocation policy with respect to computing decision, computation capacity, and transmission power. To break the time correlation of training data while accelerating the learning process of MADRL-RA, we design a weighted experience replay to store and sample experiences categorically. Furthermore, we propose a step-by-step -greedy method to balance exploitation and exploration. Finally, we verify the effectiveness of MADRL-RA by comparing it with some benchmark algorithms in many experiments, showing that MADRL-RA converges quickly and learns an effective resource allocation policy achieving the minimum system overhead.

Keywords： Multi-agent deep reinforcement learning     End–edge orchestrated     Industrial wireless networks     Delay     Energy consumption    

HTML PDF Collect

Optimization of formation for multi-agent systems based on LQR

Chang-bin Yu, Yin-qiu Wang, Jin-liang Shao,brad.yu@anu.edu.au,wh6508@gmail.com,jinliangshao@126.com

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 2,   Pages 96-109 doi: 10.1631/FITEE.1500490

Abstract: In this paper, three optimal linear algorithms are proposed for first-order linear from a perspective with cost functions consisting of both interaction energy cost and individual energy cost, because both the collective object (such as formation or consensus) and the individual goal of each agent are very important for the overall system. First, we propose the optimal formation algorithm for first-order without initial physical couplings. The parameter matrix of the algorithm is the solution to an . It is shown that the matrix is the sum of a Laplacian matrix and a positive definite diagonal matrix. Next, for physically interconnected , the optimal formation algorithm is presented, and the corresponding parameter matrix is given from the solution to a group of quadratic equations with one unknown. Finally, if the communication topology between agents is fixed, the local feedback gain is obtained from the solution to a quadratic equation with one unknown. The equation is derived from the derivative of the cost function with respect to the local feedback gain. Numerical examples are provided to validate the effectiveness of the proposed approaches and to illustrate the geometrical performances of .

Keywords： Linear quadratic regulator (LQR)     Formation control     Algebraic Riccati equation (ARE)     Optimal control     Multi-agent systems    

HTML PDF Collect

GPU-based multi-slice per pass algorithm in interactive volume illumination rendering Research Articles

Dening Luo, Yi Lin, Jianwei Zhang,onexinoneyi@hotmail.com,Yilin@scu.edu.cn,zhangjianwei@scu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 8,   Pages 1092-1103 doi: 10.1631/FITEE.2000214

Abstract: plays a significant role in medical imaging and engineering applications. To obtain an improved three-dimensional shape perception of , realistic has been considerably studied in recent years. However, the calculation overhead associated with interactive is unusually high, and the solvability of the problem is adversely affected when the data size and algorithm complexity are increased. In this study, a scalable and GPU-based (MSPP) algorithm is proposed which can quickly generate global volume shadow and achieve a translucent effect based on the transfer function, so as to improve perception of the shape and depth of . In our real-world data tests, MSPP significantly outperforms some complex volume shadow algorithms without losing the illumination effects, for example, half-angle slicing. Furthermore, the MSPP can be easily integrated into the parallel rendering frameworks based on sort-first or sort-last algorithms to accelerate . In addition, its scalable slice-based framework can be combined with several traditional frameworks.

Keywords： 体绘制；体积光照；体数据；单绘制遍多切片    

HTML PDF Collect

Title Author Date Type Operation

The Application of Multi-agent Based Distributed Intelligent Control in VAV Air Conditioning System

Zhang Hongwei,Wu Aiguo,Sheng Tao

Journal Article

Coach-assisted multi-agent reinforcement learning framework for unexpected crashed agents

Jian ZHAO, Youpeng ZHAO, Weixun WANG, Mingyu YANG, Xunhan HU, Wengang ZHOU, Jianye HAO, Houqiang LI

Journal Article

Prospects for multi-agent collaboration and gaming: challenge, technology, and application

Yu LIU, Zhi LI, Zhizhuo JIANG, You HE

Journal Article

Existence and practice of gaming: thoughts on the development of multi-agent system gaming

Qi DONG, Zhenyu WU, Jun LU, Fengsong SUN, Jinyu WANG, Yanyu YANG, Xiaozhou SHANG

Journal Article

Decentralized multi-agent reinforcement learning with networked agents: recent advances

Kaiqing Zhang, Zhuoran Yang, Tamer Başar,kzhang66@illinois.edu,zy6@princeton.edu,basar1@illinois.edu

Journal Article

A multi-agent architecture for scheduling in platform-based smart manufacturing systems

Yong-kui Liu, Xue-song Zhang, Lin Zhang, Fei Tao, Li-hui Wang,yongkuiliu@163.com,xs_zhang@126.com,zhanglin@buaa.edu.cn,ftao@buaa.edu.cn,lihuiw@kth.se

Journal Article

Designing a novel consensus protocol formultiagent systemswith general dynamics under directed networks

Hao-liang LI, Ren-nong YANG, Qiu-ni LI

Journal Article

The Mechanics of 3D Multi-body Contact System of Long Shell and Tyres

Liang Xiaoling,Xiao Yougang,Li Xuejun

Journal Article

Dynamic grouping of heterogeneous agents for exploration and strike missions

Chen CHEN, Xiaochen WU, Jie CHEN, Panos M. PARDALOS, Shuxin DING,xiaofan@bit.edu.cn,wsygdhrwxc@sina.com,pardalos@ufl.edu

Journal Article

Target detection for multi-UAVs via digital pheromones and navigation algorithm in unknown environments

Yan Shao, Zhi-feng Zhao, Rong-peng Li, Yu-geng Zhou,shaoy@zju.edu.cn,zhaozf@zhejianglab.com,lirongpeng@zju.edu.cn,yugeng.zhou@wfjyjt.com

Journal Article

Stability of General Linear Dynamic Multi-Agent Systems under Switching Topologies with Positive Real Eigenvalues

Shengbo Eben Li, Zhitao Wang, Yang Zheng, Diange Yang, Keyou You

Journal Article

Multi-agent differential game based cooperative synchronization control using a data-driven method

Yu SHI, Yongzhao HUA, Jianglong YU, Xiwang DONG, Zhang REN

Journal Article

Multi-agent deep reinforcement learning for end–edge orchestrated resource allocation in industrial wireless networks

Xiaoyu LIU, Chi XU, Haibin YU, Peng ZENG,liuxiaoyu1@sia.cn,xuchi@sia.cn,yhb@sia.cn,zp@sia.cn

Journal Article

Optimization of formation for multi-agent systems based on LQR

Chang-bin Yu, Yin-qiu Wang, Jin-liang Shao,brad.yu@anu.edu.au,wh6508@gmail.com,jinliangshao@126.com

Journal Article

GPU-based multi-slice per pass algorithm in interactive volume illumination rendering

Dening Luo, Yi Lin, Jianwei Zhang,onexinoneyi@hotmail.com,Yilin@scu.edu.cn,zhangjianwei@scu.edu.cn

Journal Article