基于多Agent的天战系统建模与仿真方法研究

简单介绍了复杂系统理论及其建模方法，分析了天战系统的总体行为特征，指出对天战系统的仿真研究需采用复杂适应系统（CAS）理论的研究方法，即采用基于Agent的建模仿真方法学来开展研究，概述了Agent和多Agent系统的概念及基于多Agent的仿真，并给出了一个基于高层体系结构（HLA）的天战系统的仿真框架，最后展望了将来的研究工作。     

基于多Agent和工作流的业务过程仿真环境

仿真是进行业务过程评价和重组的有效工具.针对目前的业务过程仿真方法的不足:不能有效地对复杂因素进行建模,不能反应复杂的任务分配策略对业务过程的影响,以及缺少分布和可扩展的仿真系统框架,提出了一个基于工作流和多Agent的业务过程仿真环境.在该环境中,人员被建模成Agent,通过Agent的属性和行为能对复杂的因素进行建模,通过Agent之间的招投标机制可以实现复杂的任务分配策略.同时,由于系统采用了基于工作流和多Agent的结构,因此具有很好的可扩展性.最后,给出了系统的实现实例.     

基于多Agent的蚂蚁觅食过程仿真研究

复杂系统的仿真研究是复杂系统研究领域的一个热点问题.研究表明,传统的建模仿真方法无法很好地刻画复杂系统,而基于多智能体(Agent)的建模仿真方法是当前研究复杂系统的最有力工具之一,有必要进行深入研究.在简单介绍复杂系统以及基于多Agent的建模仿真方法的研究概况后,以蚂蚁觅食过程为研究对象,进行基于多Agent的建模仿真实验,结果表明基本多Agent的建模仿真方法非常适合复杂系统的研究,具有很大的发展空间.     

基于Agent的语言演化仿真研究

语言的产生及其演化问题是复杂系统研究领域的一个热点问题.研究表明,传统的建模方法无法很好地刻画复杂系统,而基于多Agent的建模仿真方法是当前研究复杂系统的最有力工具之一,有必要进行深入研究.在简单介绍复杂适应性系统、基于多Agent的建模方法的研究概况,以及多Agent建模工具--Repast仿真平台以及它的结构、主要类库与建模步骤后,以语言的产生及其演化问题为研究对象,进行基于多Agent的建模仿真实验,结果表明基于多Agent的建模仿真方法非常合适复杂适应性系统的研究,具有很大的发展空间.     

基于Agent的城市废物计量收费方案仿真研究

提出一种基于Agent的城市废物计量收费仿真模型.由于城市废物计量收费仿真模型属于复杂适应性系统(CAS),传统的建模仿真方法无法完好地刻画城市废物计量收费仿真模型,而基于多Agent的建模仿真方法(ABS)是当前研究复杂适应性系统的最有利工具之一.有必要进行深入研究.在简单介绍复杂适应性系统、基于多Agent的建模方法的研究概况,以及多Agent建模工具--Repast仿真甲台以及它的结构、主要类库与建模步骤后,以城市废物计茸收费仿真模型为研究对象,进行基于多Agent的建模仿真实验,结果表明基于多Agent的建模仿真方法非常合适复杂适应性系统的研究,具有很大的发展空间.     

基于Repast Simphony平台的建模与仿真技术

随着计算机技术的发展, 基于Agent的建模与仿真技术被认为是研究复杂系统的有效方法, Repast Simphony平台为基于Agent的建模与仿真提供了有利条件. 针对如何利用Repast Simphony平台构建复杂系统仿真模型的问题, 重点介绍了Repast Simphony仿真平台, 分析了它的技术优势, 与同类仿真平台进行了比较分析, 并在分析平台主要类库的基础上, 总结出建模仿真的一般流程. 最后, 通过一个改进的Schelling模型仿真实例进一步阐述了利用平台构建复杂系统的设计与实现方法, 对使用Repast Simphony平台进行基于Agent的建模与仿真研究具有一定的指导意义.     

可配置网络式软件系统的可用性预计研究

在复杂系统的建模与仿真研究的基础上,提出了一种基于多Agent的可配置网络式软件系统的可用性预计方法。首先介绍了多Agent系统建模与仿真方法;其次分析了可配置网络式软件系统的特点;然后在研究基于多Agent的网络式软件系统建模与仿真的基础上,研究可配置的行为模型,并建立了基于多Agent的可配置网络式软件 系统可用性仿真方法;最后利用Nctlog。仿真平台,结合实例对可配置的作用进行了可用性预计,并验证了本方法的有效性。     

基于CAS理论的多Agent建模仿真方法研究进展

基于复杂适应系统CAS理论的多Agent建模仿真是近年来复杂系统领域的一个研究热点.本文在简单介绍CAS理论的基础上对基于CAS理论的多Agent建模仿真方法的主要研究内容和研究现状进行分类和描述,最后对该研究领域存在的主要问题和发展趋势进行了分析和总结.     

基于Agent的空防作战系统建模仿真方法研究

空防作战系统是一类复杂的军事作战系统.从军事作战系统的主导因素入手,讨论了传统研究方法的局限性,进而提出使用基于Agent的建模仿真(ABMS)方法研究空防作战系统的思路,并根据空防作战系统建模仿真应用的需要对ABMS进行了改进:建立了层次化的ABMS建模框架,为解决对作战动态过程的建模而引入了事件的扩展概念及其分析方法.然后介绍了一个空防作战系统建模仿真研究的完整过程,给出了系统动态演化的事件模型和作战单元的Agent模型,并针对仿真结果进行了分析;从而证明了ABMS方法的可行性和有效性.     

Repast:基于Agent建模仿真的可扩展平台

建模仿真平台为基于Agent建模理论和方法的研究创造了条件.在研究当前流行的基于Agent建模仿真平台不足的基础之上,介绍了一种新的基于Agent建模仿真平台Repast,详细阐述了该平台的设计目标、框架结构及运行机制等内容,并结合一个实例简要说明了Repast模型的设计与实现过程.该平台移植性和可扩展性强,使用方便,易于学习,方便了应用基于Agent建模仿真方法对复杂适应系统及复杂性的研究及探索,同时也为复杂适应系统的研究提供新的思路.     

基于多Agent系统的数字家庭模型研究

基于Agent的仿真是研究分布式复杂系统的重要内容,数字家庭是分布式应用的一个方面,IBMAglet是一个实现基于Agent仿真模型的软件工具。文中详细阐述了使用IBMAglet仿真平台实现数字家庭仿真模型的一般方法,探索了在IBMAglet仿真模型中的Agent和Agent交互的方法与过程。为该领域的研究者在模型实现这一问题上提供了一定的参考。     

作战仿真中坦克智能体的设计和实现

以坦克Agent实体为研究对象,根据目前作战仿真研究所面临的困难,运用基于Agent的复杂系统分析与设计方法,提出了作战仿真中坦克智能体的结构以及设计和实现方法。在分布式交互仿真HLA/RTI的技术框架和联邦开发执行标准过程(FEDEP)的规范下,构建了基于Agent的坦克对抗仿真模型,更准确的表现了战场作战实体,提高了作战仿真结果的可信度。     

Predicting Interactions Between Agents in Agent-Based Modeling and Simulation of Sociotechnical Systems

Agent-based modeling and simulation are a valuable research tools for the analysis of dynamic and emergent phenomena of large-scale complex sociotechnical systems. The dynamic behavior of such systems includes both the individual behavior of heterogeneous agents within the system and the emergent behavior arising from interactions between agents; both must be accurately modeled and efficiently executed in simulations. This paper provides a timing and prediction mechanism for the accurate modeling of interactions among agents, correspondingly increasing the computational efficiency of agent-based simulations. A method for assessing the accuracy of interaction prediction methods is described based on signal detection theory. An intelligent interaction timing agent framework that uses a neural network to predict the timing of interactions between heterogeneous agents is presented; this framework dramatically improves the accuracy of interaction timing without requiring detailed scenario-specific modeling efforts for each simulation configuration.      

复杂系统基于Agent的建模与仿真设计模式及软件框架

提出了一种基于Agent的建模与仿真设计模式——ABMS设计模式，阐述了ABMS设计模式的主要内容。该模式的提出有利于在建模与仿真领域以及软件开发界之间建立关于ABMS的对话联系与交流。然后设计了一种包含仿真服务模型ServerAgent和仿真模型结构SimAgent的ABMS分布仿真框架，该框架将最大限度实现仿真重用，并将支持大规模的基于Agent的复杂系统的仿真，包括军事对抗以及天战系统的仿真。该框架部分借鉴了HLA的思想，其中的ServerAgent提供底层的通用仿真服务。     

Care HPS: A high performance simulation tool for parallel and distributed agent-based modeling

Parallel and distributed simulation is a powerful tool for developing complex agent-based simulation. Complex simulations require parallel and distributed high performance computing solutions. It is necessary because their sequential solutions are not able to give answers in a feasible total execution time. Therefore, for the advance of computing science, it is important that High Performance Computing (HPC) techniques and solutions be proposed and studied. In literature, we can find some agent-based modeling and simulation tools that use HPC. However, none of these tools are designed to enable the HPC expert to be able to propose new techniques and solutions without great effort. In this paper, we introduce Care High Performance Simulation (HPS), which is a scientific instrument that enables researchers to: (1) develop techniques and solutions of high performance distributed simulations for agent-based models; and, (2) study, design and implement complex agent-based models that require HPC solutions. Care HPS was designed to easily and quickly develop new agent-based models. It was also designed to extend and implement new solutions for the main issues of parallel and distributed solutions such as: synchronization, communication, load and computing balancing, and partitioning algorithms. We conducted some experiments with the aim of showing the completeness and functionality of Care HPS. As a result, we show that Care HPS can be used as a scientific instrument for the advance of the agent-based parallel and distributed simulations field.     

一种时间Petri网的分布仿真算法

本文提出了一种对时间Petri网的扩展方法,并研究了其分布仿真算法。该算法适合对大型、复杂系统进行建模和仿真,并能有效地支持模型重用。     

Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations

Agent-based distributed simulations are confronted with load imbalance problem, which significantly affects simulation performance. Dynamic load balancing can be effective in decreasing simulation execution time and improving simulation performance. The characteristics of multi-agent systems and time synchronization mechanisms make the traditional dynamic load balancing approaches not suitable for dynamic load balancing in agent-based distributed simulations. In this paper, an adaptive dynamic load balancing model in agent-based distributed simulations is proposed. Due to the complexity and huge time consuming for solving the model, a distributed approximate optimized scheduling algorithm with partial information (DAOSAPI) is proposed. It integrates the distributed mode, approximate optimization and agent set scheduling approach. Finally, experiments are conducted to verify the efficiency of the proposed algorithm and the simulation performance under dynamic agent scheduling. The experiments indicate that DAOSPI has the advantage of short execution time in large-scale agent scheduling, and the distributed simulation performance under this dynamic agent scheduling outperforms that under static random agent distribution.     

Modeling and generating context-aware agent-based applications with amended colored Petri nets

Context-awareness is become more crucial in mobile distributed computing systems. However, sophisticated modeling methods to analyze context-aware systems are still very few. Among those, the Colored Petri Net (CPN) is promising because it is proven to be useful for modeling system dynamics and concurrency control in more efficient ways. However, to support managing multiple configurations of components of context-aware applications, some features need to be added to specialize the CPNs. To address these challenges, our research has two idea: (a) to decompose a system into several meaningful subsystems, each of which we will call a pattern, and (b) to separate context from the patterns to realize context-pattern independence. Hence, we propose a modeling methodology to represent and analyze a context-aware agent-based system, which tends to be highly complex. We introduce CPNs as a method of capturing the dynamics of this contextual change. We define CPNs and a way to apply them in context-aware agent-based systems. We also describe a prototype system that we have developed called CPN Generator, which translates CPN specification into Java programs.     

A framework for model-based design of agent-oriented software

Agents are becoming one of the most important topics in distributed and autonomous decentralized systems, and there are increasing attempts to use agent technologies to develop large-scale commercial and industrial software systems. The complexity of such systems suggests a pressing need for system modeling techniques to support reliable, maintainable, and extensible design. G-nets are a type of Petri net defined to support system modeling in terms of a set of independent and loosely-coupled modules. In this paper, we customize the basic G-net model to define a so-called "agent-based G-net" that can serve as a generic model for agent design. Then, to progress from an agent-based design model to an agent-oriented model, new mechanisms to support inheritance modeling are introduced. To illustrate our formal modeling technique for multiagent systems, an example of an agent family in electronic commerce is provided. Finally, we demonstrate how we can use model checking to verify some key behavioral properties of our agent model. This is facilitated by the use of an existing Petri net tool.