A function-based behavioral modeling method for air combat simulation

Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is well-suited to tackle such complex states and actions. However, it is not necessary to fuzzify the variables that have definite discrete semantics.Hence, the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchical structures from the perspective of function, namely, the functional decision tree. This method is developed to represent behavioral modeling of air combat systems, and its metamodel,execution mechanism, and code generation can provide a sound basis for function-based behavioral modeling. As a proof of concept, an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.

基于多Agent的服装可持续消费行为建模与仿真

“双碳”目标下,随着服装消费引起的气候变化和环境污染等生态问题日益严重,迫切需要重新思考和重塑服装消费模式,推动服装消费向质量型、低碳化转变,从而实现服装产业的绿色转型。文章运用多Agent建模方法,构建服装可持续消费行为仿真模型,采用Netlogo平台进行仿真实验,探求服装可持续消费行为的影响机理。结果表明,消费者可持续消费认知、产品可持续性和设施供应条件均显著促进可持续消费行为;但不同强度下,产品可持续性和设施供应条件的推动作用存在差异。基于此,从可持续消费认知和供应条件两方面提出了引导中国消费者服装可持续消费行为的建议和对策。

基于多Agent传动关系的股市趋势预测

股市趋势预测是机器学习领域中一个具有挑战性的任务。由于一些因素对于股市的影响是动态且不确定的,导致股市趋势难以预测。针对已有方法在股市预测时存在的灵敏性差、适应力弱等问题,从快变量和慢变量的传动关系出发,利用Agent技术对股市中的快周期和慢周期进行联合建模,提出一种多Agent传动影响图(MATID)股市趋势预测方法。给出股市中快周期和慢周期的划分标准,并引入周期能量的概念;通过对相关趋势指标的特征融合,给出周期能量的量化计算方法;通过分析快周期和慢周期的动态作用过程,给出传动因子的表示方法;将快周期和慢周期分别对应成不同的Agent,利用多Agent影响图模型建模快周期和慢周期的传动过程;利用股市振子模型表示快Agent和慢Agent之间的传动效用,利用联合树的自动推理技术对股市趋势进行预测。在不同样本数量和不同股市趋势下进行实验,结果表明,与门控循环单元、S-LSTM和Hybrid-RNN预测方法相比,MATID方法预测精确率提升1.5%~7.0%,召回率提升5.4%~6.7%,F1值提升3.7%~6.2%,具有良好的灵敏性和适应力。

Effect of neutral polymeric bonding agent on tensile mechanical properties and damage evolution of NEPE propellant

Introducing Neutral Polymeric bonding agents(NPBA) into the Nitrate Ester Plasticized Polyether(NEPE)propellant could improve the adhesion between filler/matrix interface, thereby contributing to the development of new generations of the NEPE propellant with better mechanical properties. Therefore,understanding the effects of NPBA on the deformation and damage evolution of the NEPE propellant is fundamental to material design and applications. This paper studies the uniaxial tensile and stress relaxation responses of the NEPE propellant with different amounts of NPBA. The damage evolution in terms of interface debonding is further investigated using a cohesive-zone model(CZM). Experimental results show that the initial modulus and strength of the NEPE propellant increase with the increasing amount of NPBA while the elongation decreases. Meanwhile, the relaxation rate slows down and a higher long-term equilibrium modulus is reached. Experimental and numerical analyses indicate that interface debonding and crack propagation along filler-matrix interface are the dominant damage mechanism for the samples with a low amount of NPBA, while damage localization and crack advancement through the matrix are predominant for the ones with a high amount of NPBA. Finally, crosslinking density tests and simulation results also show that the effect of the bonding agent is interfacial rather than due to the overall crosslinking density change of the binder.

A Cautionary Note on the Application of GIS in Spatial Optimization Modeling

Spatial optimization as part of spatial modeling has been facilitated significantly by integration with GIS techniques. However, for certain research topics, applying standard GIS techniques may create problems which require attention. This paper serves as a cautionary note to demonstrate two problems associated with applying GIS in spatial optimization, using a capacitated p-median facility location optimization problem as an example. The first problem involves errors in interpolating spatial variations of travel costs from using kriging, a common set of techniques for raster files. The second problem is inaccuracy in routing performed on a graph directly created from polyline shapefiles, a common vector file type. While revealing these problems, the paper also suggests remedies. Specifically, interpolation errors can be eliminated by using agent-based spatial modeling while the inaccuracy in routing can be improved through altering the graph topology by splitting the long edges of the shapefile. These issues suggest the need for caution in applying GIS in spatial optimization study.

探析基于公共支撑能力的政务大模型AI+Agent

本文详细探讨了具有公共支撑能力的政务大模型AI+Agent如何为政务应用赋能,点明了创新行政管理和服务方式的重要性,并根据目前省级平台建设情况,描述了系统的特点以及能力输出,最后提出了多模态大模型AI+Agent的应用场景和系统架构。

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.

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。

The Multi-Agent Modeling and Calculated Analysis of Shop Logistics Scheduling in the Manufacturing Enterprises

In this paper,the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent,process agent,testing agent,transition agent,production information agent,scheduling agent,process agent and stock agent. The scheduling agent has three subagents: manager agent (MA),resource agent (RA) and part agent (PA). MA,PA and RA are communicating equally that guarantees agility of the whole MAS system. The part tasks pass between MA,RA and PA as an integer,which can guarantee the consistency of the data. We use a detailed example about shop logistics scheduling in a semiconductor company to explain the principle. In this example,we use two scheduling strategies: FCFS and SPT. The result data indicates that the average flow time and lingering ratio are changed using different strategy. It is proves that the multi-agent scheduling is useful.

Modeling of Agile Manufacturing Execution Systems with an Agent-based Approach

Agile manufacturing execution systems (AMES) are used to help manufacturers optimize shop floor production in an agile way. And the modeling of AMES is the key issue of realizing AMES. This paper presents an agent-based approach to AMES modeling. Firstly, the characteristics of AMES and its requirements on modeling are discussed. Secondly, a comparative analysis of modeling methods is carried out, and AMES modeling using an agent-based approach is put forward. Agent-based modeling method not only inherit the favorable features of traditional object-oriented modeling method such as data encapsulation, modularity and so on, but also has the ability to construct intelligent, rational and autonomous agent which can cooperate together to realize the goal of agile operation. A general agent architecture used in AMES modeling is described. Under this architecture, an agent can be divided into domain-independent components and domain-specific components which helps solve problems such as information overload, incomplete information handling and soft decision-making. Furthermore, an AMES model using four types of agents, i.e., interface agent, information agent, resource agent and management agent, is established. Thirdly, a snapshot of AMES model is provided in the case study. Especially, an agent-based cooperating process of task scheduling in AMES is illustrated in detail. Finally, the advantages and disadvantages of this modeling approach are discussed as well.

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 Petri Nets Framework for Modeling Staphylococcus epidermidis Biofilm Formation

This Staphylococcus epidermidis has been discovered as the most frequent germ detected during indwelling medical devices infection. This fact is well attached with the ability of this bacterium to form structured layered population known as biofilm. Inside S. epidermidis biofilm, bacterial cells present more different behavior than in their planktonic counterpart. This paper describes the thriving application of Petri net theory for modeling of interaction between different regulations actors leading S. epidermidis to switch from Planctonik to Biofilm. Indeed this biologic system is very sensible and has dangerous effect. We propose Agent Petri Nets model to describe and analyze the process of formation of Biofilm molecule. This model presents a formal framework based on Multi Agents system characteristics.

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 Modeling of User Preferences Based on Fuzzy Classified ANNs in Automated Negotiation

In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user requirements to implement ecommerce activities like automated transactions.The difficulty lies in the uncertainty of user preferences that include uncertain description and contents,non-linear and dynamic variability.In this paper,fuzzy language was used to describe the uncertainty and combine with multiple classified artificial neural networks(ANNs) for self-adaptive learning of user preferences.The refinement learning results of various negotiation contracts' satisfaction degrees in the extent of fuzzy classification can be achieved.Compared to unclassified computation,the experimental results illustrate that the learning ability and effectiveness of agents have been improved.

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.

Multi-agent Based Modeling of Manufacturing Network

An intelligent manufacturing system is modeled currently from the viewpoint of manufacturing applications,and the network platform’s influence to manufacturing applications is not considered adequately. However any bottleneck in service oriented architecture (SOA) for the manufacturing network can affect the agility of the IT environment. In this paper,to achieve a trade-off between manufacturing resources and network resources,the manufacturing network is modeled with multi-agent,in which two kinds of basic elements,the manufacturing application unit and the network carrier of manufacturing information,are presented. And their main characters are described by colored petri net. The manufacturing application model drives the network platform that inversely provides this application model technology supports. The proposed multi-agent system is demonstrated through an example integration scenario involving production plan,resources management and execution subsystems. And the result suggests that analyzing and designing the system architecture of networked manufacturing should give due attention to the operation system as well as manufacturing applications.

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。

基于多Agent模型的宁东基地水-能源-粮食系统协同演化研究

随着淡水资源逐渐减少、能源需求量逐渐增长和粮食供应结构不断变化,加之三者之间既相互依存又相互竞争的特点,水-能源-粮食的交互关系变得异常复杂。为确保水安全、能源安全和粮食安全,实现三者的协同优化管理、资源的高效利用和可持续发展,以集资源型缺水和季节性缺水为一体的干旱敏感区域宁东基地为例,提出了基于多Agent模型的宁东基地水-能源-粮食系统模拟模型,将宁东基地水-能源-粮食系统看成是由若干个相对独立的自主Agent构成的一个合作共生网络体系,构建了宁东基地水-能源-粮食模拟框架,定义了各Agent的属性,设计了Agent之间以及Agent和环境要素之间的交互规则,基于Python语言的多Agent建模工具MESA库开发了宁东基地水-能源-粮食仿真模型,以模拟宁东能源化工基地的系统演化过程。结果表明:随着人口的增长,生活部门配水量、能源消耗和粮食消耗量均呈现上升趋势;粮食部门配水量呈现出与农作物产量变化相对应的变化趋势;宁东基地的能源部门配水量呈现上升趋势,预测年的配水量每年增长约为0.08亿m^(3);随着生态绿化覆盖面积的逐年增长,生态部门的配水量也呈现出逐年增长的趋势;每年可以向基地外输送的能源,实测年增长率约为19.85%,预测年增长率约为3.53%,预计到2025年可增加到4.96×107t标准煤。

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.

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.