Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.

A goal-based approach for modeling and simulation of different types of system-of-systems

A system of systems(SoS)composes a set of independent constituent systems(CSs),where the degree of authority to control the independence of CSs varies,depending on different SoS types.Key researchers describe four SoS types with descending levels of central authority:directed,acknowledged,collaborative and virtual.Although the definitions have been recognized in SoS engineering,what is challenging is the difficulty of translating these definitions into models and simulation environments.Thus,we provide a goal-based method including a mathematical baseline to translate these definitions into more effective agent-based modeling and simulations.First,we construct the theoretical models of CS and SoS.Based on the theoretical models,we analyze the degree of authority influenced by SoS characteristics.Next,we propose a definition of SoS types by quantitatively explaining the degree of authority.Finally,we recognize the differences between acknowledged SoS and collaborative SoS using a migrating waterfowl flock by an agentbased model(ABM)simulation.This paper contributes to the SoS body of knowledge by increasing our understanding of the degree of authority in an SoS,so we may identify suitable SoS types to achieve SoS goals by modeling and simulation.

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.

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.

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.

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.

COVID-19 transmission in U.S.transit buses:A scenario-based approach with agent-based simulation modeling(ABSM)

The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.

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。

高拱坝施工的SD-ABMS混合仿真建模研究

针对现有的高拱坝施工仿真多采用离散事件仿真(discrete event simulation,DES)这一建模方法,难以从微观层面精细地描述大坝施工复杂系统中的个体行为,同时仿真模型缺乏对关键连续因素的复杂作用关系进行定量分析的问题,提出高拱坝施工的SD-ABMS混合仿真建模方法。首先采用基于多智能体的仿真与建模方法(agent-based modeling and simulation,ABMS),依据高拱坝施工流程,抽象出拌和楼、自卸汽车、缆机、施工仓面四种Agent和详细的混凝土转运过程,对各Agent的行为以及它们之间的相互作用进行建模;同时,对影响施工效率的各种连续因素,基于系统动力学方法(system dynamics,SD)进行建模,定量分析疲劳、熟练度等连续影响因素对施工效率的影响;最后,以工作时间、缆机循环时间等为接口变量,建立高拱坝施工的SD-ABMS混合仿真模型。工程应用表明,与传统DES模型以及单一ABMS模型相比,仿真结果与工程实际偏差率分别平均缩小了4.83%和3.5%,为高拱坝施工过程精细化仿真分析提供了新的思路。

基于OPM与ABMS的体系架构驱动仿真方法

建模与仿真在武器装备体系研制的全过程中都发挥着非常重要的作用,但是对于如何从体系架构中提取仿真所需的数据从而驱动构造仿真系统运行的研究还比较少,无法发挥架构驱动仿真的优势。采用OPM(ObjectProcess Methodology)对武器装备体系架构进行描述,通过一定的方法从体系架构中提取ABMS(Agent Based Modeling and Simulation)仿真所需的数据,从而支持仿真的运行,继而实现利用ABMS分析武器装备体系架构并对武器装备体系的能力进行评估。

基于ABMS的员工安全意识涌现模型

为增强员工的安全意识,减少员工的不安全行为,利用复杂系统的涌现特性和多主体建模与仿真(ABMS)方法,构建员工安全意识涌现模型。运用Netlogo软件,通过调节员工、管理者、组织的主体属性值,动态模拟不同社会环境中员工安全意识的变化趋势。结果表明,安全意识是多主体交互影响的一种涌现现象,且各主体属性对员工安全意识的影响程度存在差异。受教育程度和安全培训水平对员工安全意识作用较大,管理者的情绪智力及企业对安全的重视程度次之,同时社会舆论压力对于员工安全意识存在双向影响。

Agent-based Modeling and Simulation for the Electricity Market with Residential Demand Response

Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential customers react to the price or incentive-based signals,but the actions can fall behind flexible market situations.For those residential customers equipped with smart meters,they may contribute more DR loads if they can participate in DR events in a proactive way.In this paper,we propose a comprehensive market framework in which residential customers can provide proactive RDR actions in a day-ahead market(DAM).We model and evaluate the interactions between generation companies(GenCos),retailers,residential customers,and the independent system operator(ISO)via an agent-based modeling and simulation(ABMS)approach.The simulation framework contains two main procedures—the bottom-up modeling procedure and the reinforcement learning(RL)procedure.The bottom-up modeling procedure models the residential load profiles separately by household types to capture the RDR potential differences in advance so that residential customers may rationally provide automatic DR actions.Retailers and GenCos optimize their bidding strategies via the RL procedure.The modified optimization approach in this procedure can prevent the training results from falling into local optimum solutions.The ISO clears the DAM to maximize social welfare via Karush-Kuhn-Tucker(KKT)conditions.Based on realistic residential data in China,the proposed models and methods are verified and compared in a large multi-scenario test case with 30,000 residential households.Results show that proactive RDR programs and interactions between market entities may yield significant benefits for both the supply and demand sides.The models and methods in this paper may be used by utility companies,electricity retailers,market operators,and policy makers to evaluate the consequences of a proactive RDR and the interactions among multi-entities.

On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

Occupant behavior(OB)is one of the significant sources of uncertainty in building performance simulation.While OB modeling has received increased attention in the past decade,research on the degree of granularity or level of detail(LoD)required for representing occupants is still in the nascent stages.This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment.A medium-sized prototype office building located in Chicago,Illinois is used as the simulation case study.Ten occupant-centric attributes are adopted to develop the LoDs for OB representation.We first demonstrate the different modeling approaches required for simulating the three fidelity levels.Later,we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages.This study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

融合ABM与博弈论的武汉市城镇开发边界划定与优化

城镇开发边界的划定与优化工作一直是国土空间规划改革的重要组成部分,其有助于遏制城市盲目扩张,促进资源结构有序重组。文章以武汉市为研究对象,从模拟角度探索城镇开发边界的划定与优化方法。考虑不同微观主体的偏好与目标,将多智能体模型(ABM)与元胞自动机(CA)耦合,初步划定城镇开发边界,在此基础上,引入基于博弈论的城市开发生态冲突耦合协调机制,实现划定结果的优化。研究表明:基于ABM的城镇开发边界划定方法可以深度刻画微观层面的智能体决策行为,且不同收入水平的居民智能体具有不同的偏好与目标;优化后城市用地面积为519.32 km2,新增城市用地主要集中在中心城区边缘,呈点状填充式扩展,且主城区外已出现了一定数量的卫星城,如黄陂前川、新洲邾城等。文章的研究从开发与保护的视角出发,旨在为国土空间开发格局优化提供参考。

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.

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.

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.