Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. This model was built to approximately reproduce some essential findings that were previously reported for a rather complex model of diabetes progression. Our models are translations of basicelements of this previously reported system dynamics model of diabetes. The system dynamics model, which mimics diabetes progression over an aggregated US population, was disaggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. The four estimated models attempted to replicate stock counts representing disease states in the system dynamics model while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent’s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. All three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model, although behavioral factors appeared to contribute more than the elderliness factor. The results illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.

Simulation of game analysis based on an agent-based artificial stock market re-examined

This work re-examined the simulation result of game analysis (Joshi et al., 2000) based on an agent-based model, Santa Fe Institute Artificial Stock Market. Allowing for recent research work on this artificial model, this paper’s modified game simulations found that the dividend amplitude parameter is a crucial factor and that the original conclusion still holds in a not long period, but only when the dividend amplitude is large enough. Our explanation of this result is that the dividend amplitude pa- rameter is a measurement of market uncertainty. The greater the uncertainty, the greater the price volatility, and so is the risk of investing in the stock market. The greater the risk, the greater the advantage of including technical rules.

An agent-based simulation with NetLogo platform to evaluate forward osmosis process(PRO Mode)

Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.

A Combined Discrete Event—Agent Based Approach to Modeling Tensile Strength of One-Dimensional Fibrous Materials. Face Validation and Effect of the Basic Model Parameters

A combined method of discrete event and agent based modelling has been applied to the computer modelling and simulation of the tensile strength of one-dimensional fibrous materials (ODFM). This combined method is based on the concept of discrete event simulation as being applied to the modeling of the structure of the fiber flow and on the concept of agent based modelling for modelling and simulation of the fiber interaction within the structure of the fibrous material. Frictional and traction forces arise as the result of this fiber interaction. A model of the ODFM tensile strength, which is based on the slippage effect, is created and studied in this research. Only frictional and traction forces determine the tensile strength in this kind of the model. The article examines the validation problem of the slippage effect based tensile strength model and questions regarding the strength potential estimation through variation in the parameters of the model.

Agent-Based Modeling: An Application to Natural Resource Management

Computer programs have been categorized as a useful tool to evaluate the complexity of systems. In fact, agent-based modeling (ABM) is considered a new method to model complex systems characterized by the role of independent and interrelating agents. Simulations contribute in estimating and comprehending emerging behaviors that require the development of new regulations for local agents that would make improvements to the system. This paper offers an example of a methodology and a process utilized to develop a simulation model named Befergyonet, an ABM used to conduct computer simulations within a spatio-intertemporal environment. The methodology discussed in this paper is intended solely to stimulate the use of innovative computer programs to simulate complex systems as an approach to represent real world events and may be a methodological guide for readers interested in developing their own ABM.

Simulation Technology of Environmental Impacts by Zero-energy Residential Buildings Based on Emergy Analysis Method

This paper presents a simulation technology of environmental impact for the building. By emergy analysis method,emergy costs of building( or construction engineering) can be calculated in the life cycle. It includes the engineering cost, environmental cost and social cost of building. Through integrating GIS technology with multi-agent technology,life cycle substance and energy metabolism of building( construction engineering) can be simulated and their environmental influence can be dynamically displayed. Based on the case study of entries works‘Sunny Inside'by Xiamen University in 2013 China International Solar Decathlon Competition,we discovered the changing pattern of surrounding environmental impact from waste streams of the zero-energy building and ordinary construction. The simulation results verified and showed the Odum principles of maximum power. This paper provides a new research perspective and integration approach for the environmental impact assessment in building and construction engineering. The result will help decision-making in design and construction engineering scheme.

Simulation of Old Urban Residential Area Evolution Based on Complex Adaptive System

On the basis of complex adaptive system theory, this paper proposed an agent-based model of old urban residential area, in which, residents and providers are the two adaptive agents. The behaviors of residents and providers in this model are trained with back propagation and simulated with Swarm software based on environment-rules-agents interaction. This model simulates the evolution of old urban residential area and analyzes the relations between the evolution and urban management with the background of Chaozhou city. As a result, the following are obtained ： （ 1 ） Simulation without government intervention indicates the trend of housing ageing, environmental deterioration, economic depression, and social filtering-down in old urban residential area. If the development of old urban residential area is under control of developers in market, whose desire is profit maximization, and factors such as social justice, historic and culture value will be ignored. （2） If the government carries out some policies and measures which will perfectly serve their original aims, simulation reveals that old urban residential area could be adapted to environment and keep sustainable development. This conclusion emphasizes that government must act as initiator and program maker for guiding residents and other providers directly in the development of old urban residential area.

Carbon Tax and Renewable Energy Diffusion in the Deregulated Texas Electricity Market: An Agent-Based Analysis

In the United States, emission regulations are enacted at a state level;individual states are allowed to define what methods they will use to mitigate their carbon emissions. The consequence of this is especially interesting in the state of Texas where new legislation has created a “deregulated” electricity market in which end-users are capable of choosing their electricity provider and subsequently the type of electricity they wish to consume (generated by fossil fuels or renewable sources). In this paper we analyze the effects of carbon tax on the development of renewable generation capacity at the utility level while taking into account expected adoption of rooftop PV systems by individual consumers using agent based modeling techniques. Monte Carlo simulations show carbon abatement trends and proffer updated renewable portfolio standards at various levels of likelihood.

基于PERT和ABMS的装备体系保障效能评估方法研究

装备体系的保障直接影响了装备体系的作战效果,而装备体系保障效能评估具有范围大、层次多、要素全、流程长等特点。针对飞机装备的体系化作战需求,分析了飞机装备体系保障效能评估的难点。面向飞机装备保障任务的时序性及其建模需求,设计了基于PERT的机场保障建模方法,建立了面向装备体系保障活动的PERT进程模型。提出了基于ABMS的可组合装备体系作战模型框架,定义了面向体系效能分析的保障实体类型、装备对象、交互关系和交互对象的建模概念。鉴于定性分析方法难以胜任装备体系保障的效能评估,采用基于决策树的定量分析方法分析了保障要素对体系作战效能的影响,为面向体系作战的装备保障正向设计提供了一种定量分析手段。最后,通过典型应用案例的仿真实验,验证了前述方法和模型的有效性。

基于ABMS的无人机编队协同制空任务效能评估

无人机是海空作战的重要力量,制空作战是未来无人机的重要任务之一。为研究无人机编队协同制空作战的制胜机理,评估无人机编队协同制空作战效能:首先,对无人机编队协同制空任务进行分析,明确典型作战过程;然后,采用基于Agent的建模与仿真(Agent-based modeling and simulation,ABMS)方法,构建攻击型无人机、预警型无人机和空空导弹的Agent模型,开展多无人机协同制空作战仿真和效能分析。结果表明,无人机探测距离、编队内攻击型无人机的数量,以及编队内有无预警型无人机,这些都将对作战效能产生重要影响,该结论可为无人机协同作战运用提供参考。

基于ABMS的体系效能评估框架研究

分析了基于信息系统武器装备体系基本特征和仿真评估要求,研究了基于Agent建模仿真(Agentbased modeling and simulation,ABMS)方法的体系效能仿真开发和评估过程,针对基于信息系统武器装备体系仿真评估的要求,建立了由体系效能评估准备、联合作战想定编辑、ABMS体系仿真引擎、作战过程表现及战果统计,以及体系效能综合评估等组成的体系效能评估技术参考框架,并通过开发相关系统验证了框架的合理性和实用性。

基于ABMS的矿工习惯性违章行为演化仿真

为探讨矿工习惯性违章行为(HVB)形成演化机理,基于复杂适应系统(CAS)理论、习惯领域(HD)理论和多主体建模方法(ABMS),构建HVB动态演化模型。利用Netlogo仿真平台设计仿真试验,动态模拟不同作业情境中组织、管理者、群体、矿工等多主体间的交互行为及其对HVB的影响。结果表明:矿工HVB形成演化系统是一个多主体交互作用的CAS;各主体对HVB的形成和固化作用效力有差异,安全执行力、安全督导和安全奖惩、示范性规范、安全意识对HVB形成和固化的作用效力较大。企业可通过调节各主体行为,实现HVB治理的自然演化和强制演化。

基于Multi-agent的矿工违章行为演化模型

为深入研究矿工违章行为演化机理,基于复杂适应系统(CAS)理论和多主体建模与仿真(ABMS)方法,构建矿工违章行为演化模型;利用NetLogo仿真平台,并根据矿工所处的不同工作环境,通过动态模拟组织、管理者、群体、矿工行为间的相互制约关系来表现矿工违章行为演化过程。研究表明:矿工违章行为演化系统是一个受控于多主体影响的CAS;各主体属性对矿工违章行为选择倾向度起效效果与作用力大小存在差异;工作环境因素中工作环境舒适度、环境物化程度、设备安全性水平均会直接或间接影响矿工违章行为选择倾向度。因此,在安全管理的具体实施过程中,企业可通过有效控制调节各主体行为以降低矿工违章行为选择水平。

基于Multi-agent的矿工风险感知偏差演化模型

为探索矿工风险感知偏差的形成及演化过程,在文献研究和复杂适应系统理论分析的基础上,结合多主体建模与仿真(ABMS)方法,构建矿工风险感知偏差演化模型。运用Net Logo仿真平台,通过调节组织、管理者、矿工的不同行为主体属性值,模拟组织安全文化建设水平、安全管理规范水平及风险信息处理能力对矿工风险感知偏差的动态演化过程的影响。结果表明,矿工风险感知偏差演化系统是典型的复杂适应系统(CAS);各仿真主体属性交互影响矿工风险感知偏差,且不同属性的影响程度有所差异。因此,煤炭企业应考虑各种因素的作用效果,有针对性地调节各主体行为,降低矿工风险感知偏差程度。

基于Multi-agent的矿工情绪稳定性模型构建

为解决由矿工情绪稳定性水平低下引起的不安全行为问题,基于复杂适应系统(CAS)理论和多主体建模与仿真(ABMS)的方法,构建矿工情绪稳定性水平提升模型。通过调节班组协调程度、组织公平程度、安全心理培训水平、受教育程度、个性特征和作业环境舒适度,在NETLOGO仿真平台上分析矿工意志强度、情绪安全倾向度以及管理者领导能力对矿工情绪稳定性水平的影响。研究表明:矿工的情绪稳定性水平提升系统是一种典型的复杂适应系统,矿工情绪稳定性水平是各主体属性相互作用的结果,作用程度存在差异。因此,煤炭企业应考虑各种因素,通过控制和改善各主体的行为以提高矿工情绪稳定性水平。

基于multi-agent的煤矿水害演化模型

根据矿区的水文地质条件,分析了煤矿水害事故的形成原因和演化机制,采用复杂系统理论和多主体建模方法,建立了煤矿水害演化模型;利用NetLogo仿真平台,对不同类型水害事故进行仿真模拟,动态表现煤矿水害演化过程以及影响因素之间的脆弱性关系。研究表明:煤矿水害是一种受控于多种因素、具有非线性动力特征的复杂自适应现象,只有了解矿区水文地质条件,并将复杂系统理论和多主体建模方法引入水害防治研究中,才能从本质上描述水害演化机制。

基于ABMS的CEC体系效能仿真分析

基于Agent的建模仿真(Agent Based Modeling and Simulation,ABMS)方法被普遍认为是军事作战研究特别是网络中心战(Network Centric Warfare,NCW)环境下进行作战研究的重要方法。采用ABMS仿真方法进行了CEC(Cooperative Engagement Capability)体系效能仿真分析。在体系效能分析仿真平台的支持下建立了面向CEC体系效能分析的Agent模型框架,确定了Agent实体间的探测、通信和毁伤交互关系。以舰艇编队数量和进攻强度和平台中心战(Platform CentricWarfare,PCW)、NCW和CEC指挥体制作为实验设计参数进行了批量仿真实验。通过与传统CEC体系效能分析结果的对比,发现了与传统的CEC体系效能分析研究存在的差异和原因,揭示了CEC对舰艇编队防空效能的贡献主要源于体系层次的行为控制。

基于Multi-agent的非常规突发事件下个体应激演化模型

为深入研究非常规突发事件下个体应激反应,为突发事件应急管理提供理论依据,基于复杂系统理论(CAS)和多主体建模方法(ABMS),构建了应激演化模型;利用NetLogo仿真平台,并根据个体所处的社会环境,动态模拟了非常规突发事件、群体、个体行为间的相互制约关系。研究表明:公众应激反应演化系统是一种复杂的自适应系统;非常规突发事件应激反应在三个不同阶段呈现出不同的特征。因此,在非常规突发事件的应急管理中,要根据个体在每个阶段不同的特征采取与之相适应的措施。

ABM在公共健康政策研究中的应用进展与趋势展望--基于CiteSpace文献计量分析

通过CiteSpace软件对Web of Science以及CNKI数据库收录的885篇文献进行回顾性计量分析并绘制图谱,总结国内外有关基于主体建模(ABM)于公共健康政策研究中的热点和变化趋势,为未来深化复杂健康系统相关的ABM仿真研究提供依据。结果表明:(1)国内外有关ABM于健康政策领域应用的相关研究虽总体呈现出了“运动式波动上升”的年度趋势且表现出了一定影响力但发展进程不一。(2)国内研究在机构间合作关系及融合性研究态势上较国外均不足。(3)国内外相关研究热点趋同性、差异性并存且涉及多个领域,但国内相关研究及具体应用方向较国外仍有较大拓展空间。ABM于公共健康政策研究中的应用仍面临一些挑战,未来应继续拓宽ABM方法应用的深度与广度,以解决公共健康这一复杂系统中的管理实际问题。