一种分布式智能多主体决策支持系统模型

现代大型企业的经营活动通常分布在很大的地理范围内，甚至分布于整个世界。而在诸如商业、金融、管理等复杂领域建立决策支持系统(DSS)又需要综合考虑各种数据和知识模型，以及在该领域中发生的专业认知过程的推理模式。由此，本文提出一个分布式多主体DSS(MADSS)结构，它整合了不同类型的知识表示，并且具有任务导向的学习功能。在这个模型中，此系统由分布在各地的本地子系统组成，而子系统是基于多主体技术建立的，具有独立性和协作性。子系统由各种具有不同功能和能力的主体组成。主体具有基于用例的推理(CBR)能力和任务导向的学习能力，后者主要是通过KDD技术使其及时的在企业的数据库中挖掘有用的规则，并且通过知识评价机制提升学习结果的正确性。最后，我们用一个银行贷款受理的例子来说明这个模型。     

Design Issues for Intelligent Microcomputer-Based Decision Support Systems

Microcomputer-based decision support systems (DSSs) offer many advantages over mainframe DSSs, the greatest of which is the cost7sol; benefit ratio. The use of microcomputers, however, causes numerous management control problems. Because of the limitations of microcomputers, IS managers must pay special attention to the design and implementation of microcomputer-based DSSs. With the emergence of AI technology, most managers should benefit from the integration of AI with DSSs. This article addresses issues relevant to the design of intelligent microcomputer-based DSSs from an applications standpoint. The article also presents conceptual frameworks and strategies for implementing such a system     

基于数据仓库决策分析的电力系统应用研究

首先讨论了基于数据仓库的决策分析系统的优越性,给出了一种实现模型.并就建立数据仓库的关键技术进行讨论,提出了一种新的实现数据清洗和过滤的方法,并且比较数据立方体的三种存储模型,最后给出了量化结果.     

基于数据仓库决策分析的电力系统应用研究

首先讨论了基于数据仓库的决策分析系统的优越性，给出了一种实现模型。并就建立数据仓库的关键技术进行讨论，提出了一种新的实现数据清洗和过渡的方法，并且比较数据立方体的三种存储模型，最后给出了量化结果。     

智能决策支持系统(IDSS)研究进展

在认真研究IDSS发展历史的基础上，从基于人工智能的IDSS、基于数据仓库的IDSS和IDSS的统一表示三个方面对IDSS进行分析总结，对基于人工智能的IDSS，又从专家系统、机器学习和Agent三个方面对其进行研究．认为当前IDSS研究的重点仍然是智能部件的设计与实现、各个部件之间的有效接口和系统综合集成这几方面．结合当前数据仓库、Agent等多种新技术的出现，指出综合利用多种技术来构建集成式系统是IDSS未来发展的方向．     

基于信息挖掘的智能决策支持系统的多智体结构设计

该文讨论了基于信息挖掘的智能决策支持系统IDSSIM的总体结构模型和各子系统功能描述。将领域专家的知识获取、推理机制、KDD挖掘和WEB挖掘有效地融入智能决策支持系统中,从而形成了一类具有双网、六库、综合集成、多层递阶和模型驱动的新型智能决策支持系统。     

航空维修智能决策支持系统的设计与分析

航空装备维修决策是航空维修管理的灵魂与核心,仅靠传统的工作方式和手段无法圆满完成决策任务.本文设计了一个满足各种要求,既能支持结构化决策又能支持半结构化、非结构化决策,而且能综合利用各种数据、信息、知识的智能决策支持系统.并对系统的结构进行了分解,通过实证分析,阐明系统如何进行维修方式优化.     

基于Multi-agent决策支持系统中通信和语言机制的设计和实现

通信和语言机制是研究 Multi- agent系统的基础 ,本文在分析主体特点和多主体系统的基础之上 ,设计和实现了基于 Multi- agent决策支持系统中通信和语言机制 ,包括通信机制体系结构 ,通信数据结构 ,主体连接流程以及扩展主体通信语言 EACL .并在敌情分析辅助决策支持系统应用了这套机制     

物联网环境下多智能体决策信息支持技术

随着物联网技术的不断发展,传感器网络得到了广泛的应用并成为信息技术领域重要的基础设施。尤其是传感网络提供的实时感知信息,为许多智能应用提供了充分的信息支持和必要的决策依据。然而,由于智能应用的实时感知信息需求通常无法转化为简单的查询请求与传感器底层查询接口准确匹配,因此,基于物联网的智能决策常常无法准确获取到决策相关的实时信息。针对此问题,提出一个基于语义覆盖网的物联网信息资源描述、推理和应用模型,并以多智能体系统决策支持为应用基础,研究了新型物联网环境下的多智能体决策信息支持技术。该技术以基于多智能体系统的团队导向规划的任务分解方法为核心,将复杂任务分解为若干简单子任务,并基于本体推理方法把子任务执行时需要的决策信息转化为精确、完备的传感器信息查询,从而实现从物联网中准确定位具体的传感器并获取相应感知信息的实时决策信息支持机制。     

面向并行设计的智能决策支持系统研究

基于并行设计支撑环境讨论了智能决策支持系统的重要性，论述了基于知识的并行设计过程和基于小循环的并行设计过程模型，建立了复杂产品并行智能决策支持框架，阐明了适合并行设计智能决策支持系统的领域知识描述模型，并以方案设计智能决策支持系统为例进行了验证。     

基于MAS的智能决策支持系统研究

为了使多Agent系统的研究和日益强大的网络技术为建立人机一体化的智能决策支持系统提供新的途径和方法，文中在分析了多Agent系统(MAS)体系结构的基础上，对智能决策支持系统(IDSS)进行了探讨，提出一种在网络环境下，基于MAS的智能决策支持系统模型，并给出了其决策支持过程描述、形式化定义。该模型能够为智能决策支持系统提供新的途径和方法，不仅丰富了智能决策理论，而且能够对实际决策提供有效的支持。     

面向对象的智能决策支持系统

研究如何应用面向对象技术进行智能决策支持系统的开发。首先提出面向对象智能决策支持系统的总体结构,然后介绍运用面向对象技术开发智能决策支持系统的系统分析和设计方法,最后分析了面向对象智能决策支持系统的特点,说明运用面向对象技术开发决策支持系统是有效的。     

Game Theory and Decision Theory in Multi-Agent Systems

In the last few years, there has been increasing interest from the agent community in the use of techniques from decision theory and game theory. Our aims in this article are firstly to briefly summarize the key concepts of decision theory and game theory, secondly to discuss how these tools are being applied in agent systems research, and finally to introduce this special issue of Autonomous Agents and Multi-Agent Systems by reviewing the papers that appear.     

基于多智能体的新型智能决策支持系统体系结构的产生和发展

智能决策支持系统和多智能体是近年来人工智能领域研究的热点。本文从决策支持系统的基本结构出发，针对企业科学决策的要求，介绍了三种基于多智能体的智能决策支持系统的体系结构，以实现分布式群体决策支持，具有控制Agent的群体决策支持以及大型企业的分层动态柔性决策支持。     

An effective architecture for Decision Support Systems

Decision Support Systems (DSS) are, by nature, general- purpose systems, because they must support a variety of managers who have different decision styles and different problems. However, it seems that no effective general-purpose DSS have yet come into existence, although the components of DSS such as data base technology, modeling techniques, inexpensive graphic display etc., have progressed to the point where we should now be able to build effective DSS.This shortcoming seems to result from the following fact: Research on decision support has focused on data enlargement and model refinement, however, little attention has been paid to DSS architecture which integrates these components of DSS. It has not been well appreciated that DSS architecture itself facilitates learning about unstructured-problem solving and enables system evolution.In this paper, we propose a DSS architecture based on the study of unstructured-problem solving and considerations of the needs of managers as non-computer specialists. We illustrate this with a system realized using this architecture.     

An Intelligent Decision Support System for Investment Analysis

We present an intelligent decision support system that combines decision analysis and traditional investment evaluation and analysis. The system brings to the ordinary user expertise in both decision analysis and investment evaluation techniques, as well as domain knowledge about the market. The system supports the entire decision analysis cycle and provides facilities and tools for decision modeling, probability assessment, model evaluation, and sensitivity analysis. An example based on the Shanghai Stock Market is presented. We demonstrate how an investment decision model for the stock market is constructed by the system and how the optimal decision is obtained. Sensitivity and value of information analysis were also carried out by the system. Received 12 April 1999 / Revised 8 February 2000 / Accepted 2 March 2000     

A Corporate Strategy for Decision Support Systems

Decision support systems (DSSs) attempt to bring information technology to bear on the difficult unstructured problems faced by managers. The unique characteristics of DSSs and their rapid growth raise questions for MIS planners.     

A Corporate Strategy for Decision Support Systems

Decision support systems (DSSs) attempt to bring information technology to bear on the difficult unstructured problems faced by managers. The unique characteristics of DSSs and their rapid growth raise questions for MIS planners.