Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

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.

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.

MODEL-BASED PERFORMANCE EVALUATION APPROACH FOR MOBILE AGENT SYSTEMS

Claimed as the next generation programming paradigm, mobile agent technology has attracted extensive interests in recent years. However, up to now, limited research efforts have been devoted to the performance study of mobile agent system and most of these researches focus on agent behavior analysis resulting in that models are hard to apply to mobile agent systems. To bridge the gap, a new performance evaluation model derived from operation mechanisms of mobile agent platforms is proposed. Details are discussed for the design of companion simulation software, which can provide the system performance such as response time of platform to mobile agent. Further investigation is followed on the determination of model parameters. Finally comparison is made between the model-based simulation results and measurement-based real performance of mobile agent systems. The results show that the proposed model and designed software are effective in evaluating performance characteristics of mobile agent systems. The proposed approach can also be considered as the basis of performance analysis for large systems composed of multiple mobile agent platforms.

Discrete decision model and multi-agent simulation of the Liang Zong two-chain hierarchical organization in a complex project

Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.

Design of Simulation Competition Platform Based on Cognitive Behavior Modeling

Cognitive behavior modeling of agent is an important component of simulation system,and there are some difficulties in the simulation of course teaching.When students make simulation experiments about cognitive behavior modeling,such as algorithm design and model construction,there is no simulation competition platform that is controllable,flexible and scalable.To solve this problem,we propose a simulation competition platform based on cognitive behavior modeling,called TankSim,for undergraduate and graduate students.This platform aims to cultivate studenfs team collaboration and innovation capability,and improve their learning motivation.This paper elaborates the proposed platform from three aspects,including demand analysis,platform design,and content design.

Ferroelectricity of hafnium oxide-based materials:Current status and future prospects from physical mechanisms to device applications

The finding of the robust ferroelectricity in HfO_(2)-based thin films is fantastic from the view point of both the fundamentals and the applications.In this review article,the current research status of the future prospects for the ferroelectric HfO_(2)-based thin films and devices are presented from fundamentals to applications.The related issues are discussed,which include:1)The ferroelectric characteristics observed in HfO_(2)-based films and devices associated with the factors of dopant,strain,interface,thickness,defect,fabrication condition,and more;2)physical understanding on the observed ferroelectric behaviors by the density functional theory(DFT)-based theory calculations;3)the characterizations of microscopic and macroscopic features by transmission electron microscopes-based and electrical properties-based techniques;4)modeling and simulations,5)the performance optimizations,and 6)the applications of some ferroelectric-based devices such as ferroelectric random access memory,ferroelectric-based field effect transistors,and the ferroelectric tunnel junction for the novel information processing systems.

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.

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.

Development of deep-learning-based autonomous agents for low-speed maneuvering in Unity

This study provides a systematic analysis of the resource-consuming training of deep reinforcement-learning (DRL) agents for simulated low-speed automated driving (AD). In Unity, this study established two case studies: garage parking and navigating an obstacle-dense area. Our analysis involves training a path-planning agent with real-time-only sensor information. This study addresses research questions insufficiently covered in the literature, exploring curriculum learning (CL), agent generalization (knowledge transfer), computation distribution (CPU vs. GPU), and mapless navigation. CL proved necessary for the garage scenario and beneficial for obstacle avoidance. It involved adjustments at different stages, including terminal conditions, environment complexity, and reward function hyperparameters, guided by their evolution in multiple training attempts. Fine-tuning the simulation tick and decision period parameters was crucial for effective training. The abstraction of high-level concepts (e.g., obstacle avoidance) necessitates training the agent in sufficiently complex environments in terms of the number of obstacles. While blogs and forums discuss training machine learning models in Unity, a lack of scientific articles on DRL agents for AD persists. However, since agent development requires considerable training time and difficult procedures, there is a growing need to support such research through scientific means. In addition to our findings, we contribute to the R&D community by providing our environment with open sources.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

面向任务的装备保障体系多Agent建模与评估方法

随着战争形态向着体系化、智能化转变,装备保障体系有了新挑战。同时,动态变化的战场环境要求装备体系要适应战场态势,动态支撑作战任务。目前,装备保障体系建模研究存在与作战任务联系不紧密、与装备体系不匹配,不能充分体现装备保障体系自主性等问题。首先,基于多Agent方法,从结构和流程两个方面对装备保障体系的任务层、基地层、装备层建模,重点考虑保障任务中时间和空间约束问题;其次,提出面向任务的装备保障体系评价指标,构建指标模型;最后,通过对典型作战任务对应保障活动进行仿真,验证模型的合理性和有效性,并完成装备保障体系的效能评估。本研究可为装备保障体系结构优化、流程设计等工作提供参考。

基于多Agent的在线口碑信息传播建模与仿真

在线口碑信息传播在企业社会化营销中占据重要地位,研究口碑信息传播机制及规律,对企业制定营销策略,提高企业竞争力具有重要意义。构建了一种新口碑信息传播模型De-SHIR模型,它融合了改进的传染病模型和Deffuant观点交互模型,同时基于NetLogo对新模型进行了多Agent仿真,探究口碑信息传播的宏观规律以及微观个体特质对口碑信息传播的影响。研究发现,消费者接受意愿、权威度以及网络平均度与口碑信息传播速度与规模成正相关,而从众性与口碑信息传播效果成负相关。

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.

Optimization of the Plugging Agent Dosage for High Temperature Salt Profile Control in Heavy Oil Reservoirs

After steam discharge in heavy oil reservoirs,the distribution of temperature,pressure,and permeability in different wells becomes irregular.Flow channels can easily be produced,which affect the sweep efficiency of the oil displacement.Previous studies have shown that the salting-out plugging method can effectively block these channels in high-temperature reservoirs,improve the suction profile,and increase oil production.In the present study,the optimal dosage of the plugging agent is determined taking into account connection transmissibility and inter-well volumes.Together with the connectivity model,a water flooding simulation model is introduced.Moreover,a non-gradient stochastic disturbance algorithm is used to obtain the optimal plugging agent dosage,which provides the basis for the high-temperature salting-out plugging agent adjustment in the field.

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.

病毒传播变异与人群交叉活动的相互影响及扩散模型研究

针对当前人际传染病毒高发态势,综合考虑病毒传播变异的随机特征和人群交叉活动之间的相互影响,提出并设计了多智能体模拟仿真推演模型。将病毒个体的外在致病性、传染性特征和人群个体的外在活动、免疫特征进行量化,将病毒个体与人群个体之间的相互依存及对抗过程进行建模,通过模型推演大量病毒个体和人群个体的发展趋势和统计特征。通过实验分析揭示了单个病毒变异方向的随机性不影响病毒群体变异发展方向的确定性:即病毒群体的致病性强度不断降低直到稳定在低值区间内,病毒群体的传染性强度不断升高,直到稳定在较高的数值区间内。给出了影响病毒传播变异过程的关键外在参数,可为高致病性病毒早期防控提供政策建议。

重型施工机械安拆吊装作业视觉可达性BIM仿真分析

为提高重型施工机械安拆吊装作业安全工效,改善安拆作业过程中人员的可视性,提出基于可视锥法的多主体视觉可达性建筑信息模型(BIM)仿真方法。首先,通过重型施工机械视觉任务分解,得到重型施工机械多主体视觉任务;其次,以wk-35型电铲安拆作业为研究对象,分析起重驾驶司机-信号工-司索工多主体视觉任务,运用计算机辅助三维交互应用(CATIA)人因仿真模块,构建安拆吊装作业多主体视觉的BIM仿真场景;然后,采用可视锥法,计算安拆吊装作业过程多主体视觉可达性量值,测度多主体视觉可达性水平,构建重型机械施工机械多主体视觉评价模型;最后,调节BIM模型的过程参数,推演多主体视觉变化趋势,评价安拆吊装作业多主体视觉可达性。结果表明:安拆作业中起重司机在起升下降过程中视觉可达性较差,在平移过程中视觉可达性较好;信号工和司索工的位置与其视觉可达性联系紧密,当信号工处于视野刚好覆盖起重司机和司索工的位置时,其视觉可达性最好,而司索工需不断调整位置,使其视觉可达性达到最佳。

人工草地种植策略下的草原生态变化仿真

人工草地种植是实现草地生态环境保护和牧户生活质量改善的重要途径,也是草业生产和环境治理中的重要内容之一。为了研究人工草地种植是否能达到预期的生态调节效果,该文以锡林郭勒草原的镶黄旗作为研究区域构建APG-ABM模型,模拟了五种情景下未来30年的草地发展状况,分析了牧民收入以及生态压力等指标的变化趋势。实验结果表明,未种植人工草地的情况下,牧民分别以经济效益或生态效益优先时,牧民人均收入分别在35 000元及20 000元左右,前者压力指数在[0.8,1]区间内,后者压力指数稳定在0.5以下。种植人工草地后,牧民人均收入分别达到70 000元及55 000元左右,压力指数前者在[0.7,0.9]内波动,后者稳定在0.2左右。将50%的草地资源保护后,牧民人均收入处于45 000~50 000元,生态压力处于0.5以下的正常水平。因此,人工草地的广泛种植能够使生态压力得到明显缓解,并且牧民人均收入显著提高,有利于加强中国草地生态建设。