Multiagent System Simulations of Signal Averaging in English Auctions with Two-Dimensional Value Signals

Computational experiments with a multiagent system show that bidders use signal averaging to avoid the winner’s curse in English auctions. The results vary with the percent of common value in a two-dimensional value signal, information levels, uncertainty, and the number of bidders. The complexity introduced by the combinations of these factors affects the bidding strategies and auction outcomes in interesting ways—usually nonlinearly and sometimes non-monotonically. Of main concern to a seller is the effect of these factors on revenue. I find that revenue increases with the percent of common value in the two-dimensional value signal, decreases with uncertainty, and increases with the number of bidders. There is very little impact of information level on revenue when values are pure private and pure common. However, for the intermediate cases of two-dimensional value signals, revenue decreases with increased information.      

Agent-based computational economics: modeling economies as complex adaptive systems

Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization to economics of the basic complex adaptive systems paradigm. This paper outlines the main objectives and defining characteristics of the ACE methodology, and discusses several active research areas.     

Multiagent control of self-reconfigurable robots

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.     

基于Multiagent技术的计算机市场协同咨询专家系统

本文结合作者自己的体会，收集事理知名专家的经验和意见，利用Ｍｕｌｔｉａｇｅｎｔ的新概念和技术成果，设计了一个基于因特风环境和Ｍｕｌｔｉａｇｅｎｔ技术的计算机市场协同咨询专家系统。     

基于多智能体的股票市场仿真研究

该文通过对股票市场的研究,提出采用基于多智能体的仿真方法来研究股票市场的复杂现象,并用此方法建立了股票市场的仿真模型,对模型中股民所处的环境进行了描述,定义模型中机构投资股民、技术投资股民和跟风投资股民的各种投资和行为规则,设计了股票市场对股民投资行为的撮合机制,并对模型进行了仿真,对仿真结果中股票价格的变化结果和原因,股票交易量的变化情况和原因,以及股民的行为进行了分析,最后指出了下一步的研究方向。     

多智能体一致性协议可视化仿真平台的研究

设计实现了一种通用的大规模多智能体一致性协议可视化仿真平台,介绍了平台的体系结构、工作流程、详细设计与实现,最后以舆论传播为例给出了仿真平台的测试与结果分析;提出了进行系统总体性能分析所需的性能指标,给出了具体定义,从而实现了对多智能体系统性能的分析和评价。仿真平台通过设置系统主要参数和加载对应的一致性协议,能快速进行各种一致性模型的仿真验证,再现系统的演化过程,主要的设计方法是先进行系统环境的搭建,包括智能体、网络拓扑、任务目标、一致性协议等基本要素的设计,平台还能将系统演化过程进行图形化显示,并统计整个过程所消耗的资源的信息。     

New Algorithms for Mining the Reputation of Participants of Online Auctions

The assessment of credibility and reputation of contractors in online auctions is the key issue in providing reliable environment for customer-to-customer e-commerce. Confident reputation rating system is an important factor in managing risk and building customer satisfaction. Unfortunately, most online auction sites employ a very simple reputation rating scheme that utilizes user feedbacks and comments issued after committed auctions. Such schemes are easy to deceive and do not provide satisfactory protection against several types of fraud. In this paper we propose two novel measures of trustworthiness, namely, credibility and density. We draw inspiration from social network analysis and present two algorithms for reputation rating estimation. Our first algorithm computes the credibility of participants by an iterative search of inter-participant connections. Our second algorithm discovers clusters of participants who are densely connected through committed auctions. We test both measures on real-world data and we experimentally compare them with existing solutions.     

The impact of reputation on supply chains. An analysis of permanent and discounted reputation

In long-term recurring contractual relationships, which are common in the B2B-arena, reputation and trust play a crucial role. This analysis investigates the joint impact of reputation and price-based ranking of suppliers on the material flow in the supply chain. Positive reputation proves to be a key factor in reaching dominating market positions, which illustrates the importance of building brand awareness in all stages of a supply chain. Through our simulation, it will be observed that the ranking of suppliers by reputation-based choice has a stabilizing effect on the material flow in the supply chain. A strong reputation component in the individual choice stimulates the formation of monopolies, while the discount of reputation imposes a countertendency on this effect. The Bullwhip Effect, another phenomenon that carries a countertendency to the reputation-based monopoly effect, is observed to be even stronger for members of tiers with a high fluctuation of order rates.     

火电厂Multiagent控制系统中的优化任务分解Agents

提出了一个火电厂多代理控制系统（MACS）,并洋细介绍了其中优化任务分解代理子系统（OTDAS）的目标、决策和运行,OTDAS通过一个优化代理和一个分解代理对火电厂多代理控制系统的任务进行了优化分解。优化代理的决策采用了遗传算法（GA）,OTDAS的运行结果表明GA是Agent决策的有效工具。     

The Strategic Exploitation of Limited Information and Opportunity in Networked Markets

This paper studies the effect of constraining interactions within a market. A model is analysed in which boundedly rational agents trade with and gather information from their neighbours within a trade network. It is demonstrated that a trader’s ability to profit and to identify the equilibrium price is positively correlated with its degree of connectivity within the market. Where traders differ in their number of potential trading partners, well-connected traders are found to benefit from aggressive trading behaviour. Where information propagation is constrained by the topology of the trade network, connectedness affects the nature of the strategies employed.      

Diffusion dynamics of open source software: An agent-based computational economics (ACE) approach

The rising popularity of open source software (OSS) calls for a better understanding of the drivers of its adoption and diffusion. In this research, we propose an integrated framework that simultaneously investigates a broad range of social and economic factors on the diffusion dynamics of OSS using an Agent Based Computational Economics (ACE) approach. We find that interoperability costs, variability of OSS support costs, and duration of PS upgrade cycle are major determinants of OSS diffusion. Furthermore, there are interaction effects between network topology, network density and interoperability costs, which strongly influence the diffusion dynamics of OSS. The proposed model can be used as a building block to further investigate complex competitive dynamics in software markets.     

Computational Aspects of Clearing Continuous Call Double Auctions with Assignment Constraints and Indivisible Demand

We investigate the computational complexity of clearing markets in a continuous call double auction. In the simplest case, when any part of any bid can be matched with any part of any ask, the market can be cleared optimally in log-linear time. We present two generalizations, motivated by electronic marketplaces for the process industry, where: (a) there exist assignment constraints on which bids can be matched with which asks, and (b) where demand is indivisible. We show that clearing markets with assignment constraints can be solved efficiently using network flow algorithms. However clearing markets with indivisible demand, with or without assignment constraints, requires solving NP-hard optimization problems such as the generalized assignment problem, the multiple knapsack problem and the bin packing problem.     

The Effects of Customer Value on Loyalty and Profits in a Dynamic Competitive Market

Providing high value products and services to customers normally leads to customer loyalty and profits. In practice, the relationship of customer value, loyalty, and profits can be observed in the market. However, the dynamic interactive relationships which lead to customer loyalty and profits still remain ambiguous. In this paper, the Agent-Based Computational Economics (ACE) model is introduced to explore the formation of customer loyalty in the Taiwanese imported lumber market. Using agents with reinforced learning algorithms in trading simulations, the effects of customer value on loyalty and profit are incorporated and examined in this interactive dynamic model. As results, the positive correlations among variables of customer value, loyalty, and profits are observed. A controlled experiment shows that changing customer value leads to changes in customer loyalty and profits, but price is not the determinant factor for improving customer loyalty. The R ² values of customer loyalty and profits elucidate that they are increasing as the time lapsed elongate. Providing high value of products and services is a better strategy for suppliers to attract potential loyal customers.      

基于Web的高校国库集中支付系统设计与实现

针对高校目前国库集中支付业务的现状和特点,采用B/S体系结构,设计并实现基于Web的高校国库集中支付系统。系统解决了高校国库集中支付业务信息化管理的难题。     

A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies,Procedures, and Open Problems

This paper addresses the methodological problems of empirical validation in agent-based (AB) models in economics and how these are currently being tackled. We first identify a set of issues that are common to all modelers engaged in empirical validation. We then propose a novel taxonomy, which captures the relevant dimensions along which AB economics models differ. We argue that these dimensions affect the way in which empirical validation is carried out by AB modelers and we critically discuss the main alternative approaches to empirical validation being developed in AB economics. We conclude by focusing on a set of (as yet) unresolved issues for empirical validation that require future research.      

基于安全机制的财税库银联网系统的设计与实现①

财税库银联网系统是联系财政、税务和人民银行、商业银行的大型数据库应用系统,保证系统的安全稳定运行是非常重要的。根据系统面临的安全风险的特点,提出了计算机硬件、网络传输、数据库管理系统和密码学具体应用的方法,这些方法加强了财税库银联网系统的安全机制,保证了税款的安全、及时缴入国库。     

An agent-based simulation model for analyzing the governance of the Brazilian Financial System

Regulation can play an important role in effectively managing systemic risk while providing accountability to all affected governments. IMF points out weak governance structures as one of the main causes for financial/economical crisis. However, research in this area is still limited. One of the reasons is the inherent complexity of the public sector governance notion. In this research, the regulatory governance of the financial sector is conceived as a complex system, in which governance is perceived as a phenomenon resulting from the interactions among all the actors that influence or are influenced by regulatory activities within the financial sector. An agent-based simulation was developed to analyze and evaluate the emergent behaviors from the governance in the Brazilian finance sector under different macroeconomics variables and different attitudes, perceptions and desires of economic and political actors. The agent-based model is combined with an econometric model, which is intended to characterize the macroeconomic environment. The regulatory environment is modeled by computational agents using BDI (beliefs–desires–intentions) architecture. The agents have beliefs about their environment and desires they want to satisfy, thus leading them to create intentions to act. The agents’ behavior was modeled using fuzzy rules built by means of content analysis of newspapers and in-depth interviews with experts from the financial area. Computational experiments demonstrate the potential of the agent-based model simulation in the study of complex environments involving regulatory governance.     

Computational intelligence in economics and finance: Carrying on the legacy of Herbert Simon

This is an editorial guide for the special issue on computational intelligence (CI) in economics and finance. A historical introduction to the background is given. This research paradigm is traced back to Herbert Simon, who, as a founder of artificial intelligence, pioneered the applications of AI to economics. The move from the classical AI to CI indicates a continuation of the legacy of Herbert Simon. Computational intelligence has proved to be a constructive foundation for economics. In responding to what Herbert Simon referred as procedural rationality, our study of bounded rationality has been enriched by bringing autonomous agents into the economic analysis.     

闭环控制系统的高精度快速测速算法

分析了高精度速度闭环测控系统中的计算时延及其对系统性能的影响,结合编码器周刻线数的特点,采用了一种新颖的简化计算方法.在保证分辨力的前提下,减少速度计算工作量,缩短计算时间,可提高采样频率,拓宽测量范围.在特种工程车的闭环速度控制系统中获得成功应用.     

基于NS-2的网络控制系统仿真研究及实现

基于网络仿真软件NS-2的编程通用性强和功能可扩展的特点,该文探讨了在信息调度下利用NS软件进行网络控制系统仿真的方法和设计实现过程。在此问题中,充分利用了NS-2仿真中的离散事件驱动方式,实现了网络控制系统的变速率采样模式。利用NS-2中类C＋＋的语言环境实现了变速率采样模式下控制系统微分方程的实时求解,并结合在网络信道容量有限而对控制系统信息进行调度的假设下,进一步仿真验证了保持控制系统稳定和进行变速率采样的控制算法。最后展示了仿真研究的结果。