Flocking in Multi-Agent Systems with Multiple Virtual Leaders Based Only on Position Measurements

Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring agents. In this paper, the problem of controlling a flock of mobile autonomous agents to follow multiple virtual leaders is investigated by using only position information in the sense that agents with the same virtual leader asymptotically attain the same velocity and track the corresponding virtual leader based on only position measurements. A flocking algorithm is proposed under which every agent asymptotically attains its desired velocity, collision between agents can be avoided, and the final tight formation minimizes all agents' global potentials. A simulation example is presented to verify and illustrate the theoretical results.     

Controllability of Discrete-Time Multi-Agent Systems with Multiple Leaders on Fixed Networks

This paper investigates controllability of discrete-time multi-agent systems with multiple leaders on fixed networks. The leaders are particular agents playing a part in external inputs to steer other member agents. The followers can arrive at any predetermined configuration by regulating the behaviors of the leaders. Some sufficient and necessary conditions are proposed for the controllability of discrete-time multi-agent systems with multiple leaders. Moreover, the case with isolated agents is discussed. Numerical examples and simulations are proposed to illustrate the theoretical results we established.     

Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph

This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents,and agents will pursue the target once they detect its existence. Since the ability of each agent may be different,we consider the heterogeneous multi-agent systems. According to the topology of the multi-agent systems,a novel consensus-based control law is proposed,where the target and agents are modeled as a leader and followers,respectively. Based on Mason’s rule and signal flow graph analysis,the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally,simulation studies are provided to verify the effectiveness of the proposed approach.     

Consensus of heterogeneous multi-agent systems with linear and nonlinear dynamics

In this paper, we perform an in-depth study about the consensus problem of heterogeneous multi-agent systems with linear and nonlinear dynamics.Specifically, this system is composed of two classes of agents respectively described by linear and nonlinear dynamics. By the aid of the adaptive method and Lyapunov stability theory, the mean consensus problem is realized in the framework of first-order case and second-order case under undirected and connected networks.Still, an meaningful example is provided to verify the effectiveness of the gained theoretical results. Our study is expected to establish a more realistic model and provide a better understanding of consensus problem in the multi-agent system.     

Leader-following formation control of multi-agent networks based on distributed observers

To investigate the leader-following formation control, in this paper we present the design problem of control protocols and distributed observers under which the agents can achieve and maintain the desired formation from any initial states, while the velocity converges to that of the virtual leader whose velocity cannot be measured by agents in real time. The two cases of switching topologies without communication delay and fixed topology with time-varying communication delay are both considered for multi-agent networks. By using the Lyapunov stability theory, the issue of stability is analysed for multi-agent systems with switching topologies. Then, by considering the time-varying communication delay, the sufficient condition is proposed for the multi-agent systems with fixed topology. Finally, two numerical examples are given to illustrate the effectiveness of the proposed leader-following formation control protocols.     

Asymptotic bounded consensus tracking of double-integrator multi-agent systems with bounded-jerk target based on sampled-data without velocity measurements

This paper investigates asymptotic bounded consensus tracking(ABCT) of double-integrator multi-agent systems(MASs) with an asymptotically-unbounded-acceleration and bounded-jerk target(AUABJT) available to partial agents based on sampled-data without velocity measurements. A sampled-data consensus tracking protocol(CTP) without velocity measurements is proposed to guarantee that double-integrator MASs track an AUABJT available to only partial agents.The eigenvalue analysis method together with the augmented matrix method is used to obtain the necessary and sufficient conditions for ABCT. A numerical example is provided to illustrate the effectiveness of theoretical results.     

NETEST: Estimating a Terrorist Network's Structure—Graduate Student Best Paper Award, CASOS 2002 Conference

Since the events of September 11, 2001, the United States has found itself engaged in an unconventional and asymmetric form of warfare against elusive terrorist organizations. Defense and investigative organizations require innovative solutions that will assist them in determining the membership and structure of these organizations. Data on covert organizations are often in the form of disparate and incomplete inferences of memberships and connections between members. NETEST is a tool that combines multi-agent technology with hierarchical Bayesian inference models and biased net models to produce accurate posterior representations of a network. Bayesian inference models produce representations of a network's structure and informant accuracy by combining prior network and accuracy data with informant perceptions of a network. Biased net theory examines and captures the biases that may exist in a specific network or set of networks. Using NETEST, an investigator has the power to estimate a network's size, determine its membership and structure, determine areas of the network where data is missing, perform cost/benefit analysis of additional information, assess group level capabilities embedded in the network, and pose what if scenarios to destabilize a network and predict its evolution over time.     

日常择路行为的多智能体模拟

日常路径选择是一个长期的、多体参与的非合作博弈过程.基于多智能体环境，对交通信息公开和不公开两种路径更新规则进行了模拟研究，结果表明，信息公开比不公开能够使路径流量更快地演化到logit随机用户均衡状态，但若对信息的依赖程度过大，则可能导致系统振荡；出行者完全依靠自身经验完成路径选择也可以使系统演化至稳定态，但代价是演化效率太低.因此，既要公开交通信息，又要注意合理使用信息.     

基于黑板模型和多Agent的导航设备数字维修平台

为了解决目前导航设备维修保障工作中存在的维修资源分散、维修效率较低等问题，新建了基于Web的导航设备数字维修平台，分别设计了远程查询Agent、远程推理Agent、远程测试Agent等功能子模块。各Agent功能自治，有利于模块化设计和系统扩展。多Agent联合则可以提高系统的分布计算能力和整体性能。针对远程查询、推理、测试等多Agent通信问题，提出了一种易于实现的应用层黑板模型，采用Microsoft SQL Server数据库表保存黑板消息，作为多Agent信息交换的中介。黑板消息的读取和写入操作，采用ADO-NET数据库访问驱动来实现，避免了编写复杂的会话层通信程序。     

Common Owning,Transmission, and Development of Knowledge

This paper studies the relationship between social institutions and individual behaviour through the development of the cognitive framework of individuals. Social sciences have had interests in social institutions or norms. Much of the studies treat the problem from the viewpoint of social costs and lack focus on individual action and cognition. To consider the problem as a whole naturally means that the discussion has to be made according to subjectivism. Setting subjectivism forth as a premise, the problem of relativity of the cognition is studied through reconsideration of the conception of information and its transfer. By adopting a multi-agent model having the cognitive framework and the interaction among agents, the formation process and the feature of institutions are computationally investigated. Simulation results confirm that the cognitive frameworks of agents are affected action mimicking others' superficial behaviour. Moreover, it is eventually shown that the assumption of isolated individuals is unwarranted even in studying in less communicative communities.