基于Agent的电动汽车电池回收模型研究

运用Agent理论及多主体系统理论,建立了电动汽车废旧电池CDDM(消费者-汽车分销商-电池分销商-电池制造商)的回收模式,通过在AnyLogic软件上的建模与仿真实验,得出该回收模式能够减少对新电池的需求,并减少大约60%的废弃电池产生量,使循环使用的电池量增加32.2%。     

Knowledge integration and network formation

In this paper, we highlight how inter-firm collaboration networks are influenced by the knowledge composition of goods in an industry. For this purpose, we carry out an agent-based simulation study in which firms integrate their competencies under different knowledge-based regimes. In this way networks form. The results reveal that knowledge regime significantly influences the network structure, and interaction among firms not only is very intensive when the products are specialized but also have common knowledge among them.     

基于Agent的工作流管理系统研究

介绍了工作流技术的相关概念和工作流管理系统的系统特性。分析了Agent的特性和优点，给出了基于Agent的工作流系统模型并对其中Agent的进行了功能分析。提出了集中式体系结构和分布式体系结构并针对其中的不足引入了Agent技术，通过对Agent过程实例执行的分析，说明了Agent技术对工作流管理系统的改进。     

The accounting practices of a sixteenth-century pastel merchant from the French region of Toulouse

Until the end of the sixteenth century the French region of Toulouse was an important centre for the export of pastel, the plant used at that time to produce blue dye. What does the ledger belonging to the factor of a Toulouse pastel producer (pastelier) teach us about the role played by accounting in the relationship between the factor and the commissioning merchant? Under what accounting methods did the agent carry out his business mission? Was the accounting technique used double entry or that which we could call the factors' accounting system?     

Flood decision support system on agent grid: method and implementation

In this paper, we introduce the concept and architecture of agent grid. Agent grid is an intelligent platform that enables the independent operating entities (agents) to interact with one another to form dynamic services on the Grid. Under this view, we built an agent grid platform named AGrIP that includes four layers and several useful toolkits. With the platform support, we implemented the flood decision support system which combines the wireless sensor network for data acquisition and software agent technology for legacy system integration. Additionally, we developed a toolkit for programmers to visually develop software agents which makes the development process easier. Besides, the MWAC model proposed is for sensor network to save power which can transit the information for long distance. This system is now applied as a module in the city emergency interact project.     

基于物流外包的信息支持系统的设计和规划

首先对供应链管理环境下的物流外包合作主体之间的关系特征进行了研究,并据此提出了与之相适应的信息支持系统应具备的功能,指出一个良好的物流外包信息支持系统应该能够满足参与方相互协作并保持各自独立性的需要,采取了互联网技术和多Agent技术架构对物流服务外包信息支持系统的结构进行设计和规划,并对该系统中各Agent之间的通信模型和协调机制进行了重点研究,接着根据物流服务外包中相关业务的协调规则和资源调度规则,对信息支持系统框架中各个Agent之间的状态激活流程和机制进行了详细的分析和研究.     

The minimal model of financial complexity

A representative investor generates realistic and complex security price paths by following this trading strategy: if, a few ticks ago, the market asset had two consecutive upticks or two consecutive downticks, then sell, and otherwise buy. This simple, unique, and robust model is the smallest possible deterministic model of financial complexity, and its generalization leads to complex variety. Compared to a random walk, the minimal model generates time series with fatter tails and more frequent crashes, thus more closely matching the real world. It does all this without any parameter fitting.     

A computational view of market efficiency

We study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be efficient with respect to resources S (e.g., time, memory) if no strategy using resources S can make a profit. As a first step, we consider memory-m strategies whose action at time t depends only on the m previous observations at times t???m,?…?,?t???1. We introduce and study a simple model of market evolution, where strategies impact the market by their decision to buy or sell. We show that the effect of optimal strategies using memory m can lead to ‘market conditions’ that were not present initially, such as (1) market spikes and (2) the possibility for a strategy using memory m′?>?m to make a bigger profit than was initially possible. We suggest ours as a framework to rationalize the technological arms race of quantitative trading firms.     

Simulating the adoption of fuel cell vehicles

Supply security and environmental concerns associated with oil call for an introduction of hydrogen as a transport fuel. To date, scenario studies of infrastructure build-up and sales of fuel cell vehicles (FCVs) are driven by cost estimates and technological feasibility assumptions, indicating that there is a “chicken and egg problem”: Car producers do not offer FCVs as long as there are no hydrogen filling stations, and infrastructure will not be set up unless there is a significant number of FCVs on the road. This diffusion barrier is often used as an argument for a major (public) infrastructure program, neglecting the fact that the automobile market is highly competitive and car producers, consumers, and filling station operators form an interdependent dynamic system, where taxes influence technology choice. In this paper, an agent-based model is used that captures the main interdependencies to simulate possible diffusion paths of FCVs. The results suggest that a tax on conventional cars can successfully promote diffusion even without a major infrastructure program. However, consumers and individual producers are affected differently by the tax, indicating that differently strong resistance towards such a policy can be anticipated. Moreover, there is evidence that some producers might benefit from cooperation with filling station operators to generate a faster build-up of infrastructure.