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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    

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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    

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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    

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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    

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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    

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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    

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Survey on Particle Swarm Optimization Algorithm

Yang Wei,Li Chiqiang

Strategic Study of CAE 2004, Volume 6, Issue 5,   Pages 87-94

Abstract:

Particle swarm optimization (PSO) is a new optimization technique originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. PSO can be implemented with ease and few parameters need to be tuned. It has been successfully applied in many areas. In this paper, the basic principles of PSO are introduced at length, and various improvements and applications of PSO are also presented. Finally, some future research directions about PSO are proposed.

Keywords： swarm intelligence     evolutionary algorithm     particle swarm optimization    

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Optimal synchronization control for multi-agent systems with input saturation: a nonzero-sum game Research Article

Hongyang LI, Qinglai WEI

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 1010-1019 doi: 10.1631/FITEE.2200010

Abstract: This paper presents a novel method for with . The multi-agent game theory is introduced to transform the problem into a multi-agent . Then, the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman (HJB) equations with nonquadratic input energy terms. A novel method is presented to obtain the Nash equilibrium solution without the system models, and the critic neural networks (NNs) and actor NNs are introduced to implement the presented method. Theoretical analysis is provided, which shows that the iterative control laws converge to the Nash equilibrium. Simulation results show the good performance of the presented method.

Keywords： Optimal synchronization control     Multi-agent systems     Nonzero-sum game     Adaptive dynamic programming     Input saturation     Off-policy reinforcement learning     Policy iteration    

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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    

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Institutionalized and systematized gaming for multi-agent systems Editorial

Jun LU, Fei-Yue WANG, Qi DONG, Qinglai WEI

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 7,   Pages 991-994 doi: 10.1631/FITEE.2240000

Abstract: Multi-agent system gaming (MASG) is widely applied in military intelligence, information networks, unmanned systems, intelligent transportation, and smart grids, exhibiting systematic and organizational characteristics. It requires the multi-agent system perceive and act in a complex dynamic environment and at the same time achieve a balance between individual interests and the maximization of group interests within the system. Some problems include complex system structure, uncertain game environment, incomplete decision information, and unexplainable results. As a result, the study of multi-agent game has transformed from a traditional simple game to a game facing a high-dimensional, continuous, and complex environment, which prompts an urgent need for institutionalized and systematized gaming (InSys gaming). With this background, several important tendencies have emerged in the development of InSys gaming for multi-agent systems:1. Analyzing the evolution law of MASG and establishing the InSys gaming theory model for multi-agent systemsThe organized and systematic MASG has orderly and structured characteristics, so it is necessary to establish a system game model. To study political, military, economic, and other systemic confrontation gaming problems, the first step is to analyze the system’s internal evolution characteristics and external interaction information. In addition, establishing the evolution model of InSys gaming and studying the elements, relationships, and criteria of the game evolution help provide theoretical support for the system design, decision-making planning, and other research in this field.2. Combining several artificial intelligence learning algorithms to achieve collaborative decision-making of multi-agent systemsThe current mainstream artificial intelligence learning methods all have application advantages in specific scenarios. In solving InSys gaming problems, we can combine the environmental representation ability of deep learning and the decision generation ability of reinforcement learning (RL). For example, by building a digital simulation training environment, intelligent decision algorithms and unsupervised training methods can be designed to generate a multi-agent system’s collaborative decision in a complex and unknown environment.3. Adopting a hierarchical task planning and decision-making action architecture to reduce the complexity of collaborative decision-making algorithmsWith the increase of the scale of multi-agent systems, the problems of node coupling, observation uncertainty, and interaction disorder faced by collaborative decision-making have become increasingly prominent. The complexity of solving its systematic and organized game problems has increased significantly. A multi-agent hierarchical algorithm architecture is constructed through game task decomposition, longterm planning, and real-time action decision-making. It can effectively reduce the complexity of the search process of a collaborative decision-making algorithm. In addition, it is a feasible idea for solving an organized and systematic game.4. Establishing the robustness analysis framework of the algorithm model to solve the model deviation between data-driven methods and the actual sceneWhen the training data deviates from the actual scene for data-driven methods, the algorithm’s performance will be degraded. Thus, it is necessary to study the robustness analysis framework of data-driven methods. For example, a robust algorithm model and an actual data fine-tuning method are designed to reduce the performance loss of the trained algorithm. This strategy helps support the actual deployment of data-driven methods.Game theory has become a basic analytical framework for solving problems in strategic politics, military confrontation, market economy, and so on. The object of analysis is characterized by complex systematization and organization and has been highly concerned with and valued by academic and industrial circles alike. A multi-agent system is used to model the organized and systematic game, combined with an artificial intelligence method to solve the game decision-making problem, providing a new idea for developing theories, methods, and technologies in this field.
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Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets Research Article

Bin HE, Hongtao SU,aihebin19@163.com,suht@xidian.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 617-629 doi: 10.1631/FITEE.2000652

Abstract: To deal with the threat of the new generation of electronic warfare, we establish a non-cooperative countermeasure game model to analyze and interference suppression between multistatic multiple-input multiple-output (MIMO) radars and in this study. First, according to the strategy, a supermodular game framework with a fixed weight (FW) vector is constructed. At the same time, a constrained optimization model for maximizing the radar utility function is established. Based on the utility function, the best strategies for the radars and jammers are obtained. The existence and uniqueness of the Nash equilibrium (NE) of the are proved. A algorithm with FW is proposed which converges to the NE. In addition, we use adaptive methods to suppress cross-channel interference that occurs as direct wave interferences between the radars and jammers. A algorithm for joint and is also proposed. The algorithm can ensure the best , and also improves the interference suppression ability of the . Finally, the effectiveness and convergence of two algorithms are verified by numerical results.

Keywords： Supermodular game     Power allocation     Beamforming     MIMO radar     Multiple jammers    

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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    

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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    

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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    

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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    

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Title Author Date Type Operation

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

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

Yu LIU, Zhi LI, Zhizhuo JIANG, You HE

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

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

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

Survey on Particle Swarm Optimization Algorithm

Yang Wei,Li Chiqiang

Journal Article

Optimal synchronization control for multi-agent systems with input saturation: a nonzero-sum game

Hongyang LI, Qinglai WEI

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

Institutionalized and systematized gaming for multi-agent systems

Jun LU, Fei-Yue WANG, Qi DONG, Qinglai WEI

Journal Article

Supermodular interference suppression game for multistatic MIMO radar networks and multiple jammers with multiple targets

Bin HE, Hongtao SU,aihebin19@163.com,suht@xidian.edu.cn

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