On Consensus and Stability under Denial-of-Service Attacks

In the paper, discrete-time multi-agent systems under Denial-of-Service (DoS) attacks are considered. Since in the presence of DoS attacks the stability of the whole system may be disturbed, sufficient stability conditions for the multi-agent system under DoS attacks are delivered. The consensus problem for the special case of the considered system under DoS attacks is also examined by delivering sufficient conditions. Theoretical considerations are illustrated by numerical examples.     

KnowRU: Knowledge Reuse via Knowledge Distillation in Multi-Agent Reinforcement Learning

Recently, deep reinforcement learning (RL) algorithms have achieved significant progress in the multi-agent domain. However, training for increasingly complex tasks would be time-consuming and resource intensive. To alleviate this problem, efficient leveraging of historical experience is essential, which is under-explored in previous studies because most existing methods fail to achieve this goal in a continuously dynamic system owing to their complicated design. In this paper, we propose a method for knowledge reuse called “KnowRU”, which can be easily deployed in the majority of multi-agent reinforcement learning (MARL) algorithms without requiring complicated hand-coded design. We employ the knowledge distillation paradigm to transfer knowledge among agents to shorten the training phase for new tasks while improving the asymptotic performance of agents. To empirically demonstrate the robustness and effectiveness of KnowRU, we perform extensive experiments on state-of-the-art MARL algorithms in collaborative and competitive scenarios. The results show that KnowRU outperforms recently reported methods and not only successfully accelerates the training phase, but also improves the training performance, emphasizing the importance of the proposed knowledge reuse for MARL.     

有leader的二阶动态多智能体网络的L2—L∞控制

考虑系统噪声和时滞,利用L₂—L_∞控制理论研究了有leader的二阶定拓扑多智能体系统的协调一致问题.工程应用中控制输出的极大值经常需控制在一定范围内,并且考虑系统对位置变量和速度变量限制的范围不同,分别针对位置和速度的控制输出设计了加权系数;进而建立了多智能体系统的数学模型.对有时滞和无时滞的两种网络拓扑,利用李亚普诺夫函数,分析了多智能体系统在满足L₂—L_∞性 关键词： L₂—L_∞控制')" href="#">L₂—L_∞控制 多智能体系统 一致问题 时滞     

Robust fixed-time consensus protocols for multi-agent systems with nonlinear state measurements

This paper solves the robust fixed-time consensus problem for multi-agent systems with nonlinear state measurements. Sufficient conditions are established for the proposed protocol to reach fixed-time consensus under time-varying undirected and fixed directed topology with the aid of Lyapunov functions. It is proved that the finite settling time of the presented protocol for robust consensus is uniformly bounded for any initial condition, which makes it possible for people to design and estimate the convergence time off-line. Numerical simulations are preformed to show the effectiveness of our proposed protocol.     

基于多主体的股市模型不同市场形态下的标度行为

利用理论分析和计算机仿真相结合的方法研究一个随机多主体的股市模型,理论分析得到基础价值均衡、非基础价值均衡、周期和混沌四种市场形态的典型参数设置,基于多主体的计算机仿真产生对应参数的价格序列.对此数据的统计分析发现:股市的所有市场形态都呈现收益率分布和波动时间依赖的标度行为,其中基础价值均衡形态下收益率累积分布指数和波动时间依赖的自相似指数最大,非基础价值均衡形态下两指数最小,周期和混沌形态下居中.     

Leaderless and leader-following consensus of multi-agent chaotic systems with unknown time delays and switching topologies

In this paper the distributed consensus problem for a class of multi-agent chaotic systems with unknown time delays under switching topologies and directed intermittent communications is investigated. Each agent is modeled as a general nonlinear system including many chaotic systems with or without time delays. Based on the Lyapunov stability theory and graph theory, some sufficient conditions guarantee the exponential convergence. A graph-dependent Lyapunov proof provides the definite relationship among the bound of unknown time delays, the admissible communication rate and each possible topology duration. Moreover, the relationship reveals that these parameters have impacts on both the convergence speed and control cost. The case with leader-following communication graph is also addressed. Finally, simulation results verify the effectiveness of the proposed method.     

基于可变航速的支线集装箱船舶调度优化模型与算法

随着航运市场的竞争不断加剧和集装箱船舶大型化的发展,越来越多的航运企业选择轴-辐式航运网络模式。支线船舶调度问题作为轴-辐式航运网络的重要组成部分受到研究者的高度关注。本文研究了可变航速和经济航速两种情境下的支线船舶调度问题,同时考虑枢纽港和喂给港的取送箱时间窗限制,以航运企业运营成本最小化为目标函数建立非线性混合整数规划模型。首先使用专业的规划求解器进行小规模算例的求解,验证了模型的准确性。同时运用改进的遗传算法对大规模支线船舶优化调度模型进行求解。为了提高求解效果,进一步设计了多智能体进化算法进行求解。数值结果表明,可变航速的运营成本低于经济航速的运营成本;在算法效率方面,改进遗传算法收敛速度较快,多智能体进化算法则可以提高求解精度。     

Fault-tolerant finite-time dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure

This paper investigates fault-tolerant finite-time dynamical consensus problems of double-integrator multi-agent systems (MASs) with partial agents subject to synchronous self-sensing function failure (SSFF). A strategy of recovering the connectivity of network topology among normal agents based on multi-hop communication and a fault-tolerant finite-time dynamical consensus protocol with time-varying gains are proposed to resist synchronous SSFF. It is proved that double-integrator MASs with partial agents subject to synchronous SSFF using the proposed strategy of network topology connectivity recovery and fault-tolerant finite-time dynamical consensus protocol with the proper time-varying gains can achieve finite-time dynamical consensus. Numerical simulations are given to illustrate the effectiveness of the theoretical results.     

The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region

The initial version of the model used in this study, Village 1.0, was implemented by Tim Kohler and a team of developers mostly from Washington State University. The original model addressed environmental constraints only and did not attempt to model social interaction. In a recent paper we employed Cultural Algorithms as a framework in which to add selected social considerations. In this paper we extend our previous model by adding the ability of agents to perform symmetrically initiated or asymmetrically initiated generalized reciprocal exchange. We have developed a state model for agents' knowledge and, given agents' different responses based on this knowledge. Experiments have shown that the network structure of the systems without reciprocity was the simplest but least resilient. As we allowed agents more opportunities to exchange resources we produced more complex network structures, larger populations, and more resilient systems. Furthermore, allowing the agents to buffer their requests by using a finite state model improved the relative resilience of these larger systems. Introducing reciprocity that can be triggered by both requestors and donors produced the largest number of successful donations. This represents the synergy produced by using the information from two complementary situations within the network. Thus, the network has more information with which it can work and tended to be more resilient than otherwise.