基于对象／Agent的计算机集成过程运行系统建模研究

运用面向对象方法学、ＫＡＤＳ原理以及分布式人工智能领域的Ａｇｅｎｔ概念,用对象描述过程领域,用Ａｇｅｎｔ描述过程运行决策系统,建立一种基于对象／Ａｇｅｎｔ的计算机集成过程运行（ＣＩＰＯ）系统模型。通过开发实例系统ＴＥ－ＣＩＰＯＳ,说明了该模型的应用及优点。     

基于BDI模型构建信息Agent

本文提出一种用于分布式多Ａｇｅｎｔ环境的以ＢＤＩ模型为基础构建信息Ａｇｅｎｔ的方法,给出了ＰＥＲＦＯＲＭ（ＰＥＲｓｏｎａｌ ｉｎＦＯＲｍａｔｉｏｎ Ｍａｎａｇｅｒ）系统的模型和算法。     

基于Agent 方法体系的ODSS 研究

通过组织与多Ａｇｅｎｔ系统的比较,指出组织问题的研究与多Ａｇｅｎｔ系统可以相互借鉴;对组织决策进行分析,指出组织知识、组织智能对组织决策的重要性;在此基础上,提出在组织环境下基于多Ａｇｅｎｔ系统的ＯＤＳＳ层次模型。     

移动Agent系统综述

移动Ａｇｅｎｔ系统是一种崭新的分布式计算和网络通讯的模式,介绍了移动Ａｇｅｎｔ的概念和移动Ａｇｅｎｔ系统与其它相关技术的比较,强调了移动Ａｇｅｎｔ系统所必须解决的几个关键问题,同时分析了现有的几个实际的移动Ａｇｅｎｔ系统,对移动Ａｇｅｎｔ系统的应用进行了展望。     

面向装配的多Agent协同设计研究

分析了面向装配设计（ＤＦＡ）技术发展和存在的问题,提出了ＤＦＡ中多Ａｇｅｎｔ协同设计研究的必要性。对设计Ａｇｅｎｔ的概念、结构及设计过程进行了描述和研究,并在此基础上对多Ａｇｅｎｔ协同设计过程和表示做了进一步的研究。最后,对面向ＤＦＡ的多Ａｇｅｎｔ协同原型设计系统进行了设计。     

一种实现互操作的分布式集成框架的设计与实现

互操作性问题是分布计算中需要解决的关键问题。这一问题可以通过多种途径加以解决,其中面向对象的集成框架是一种比较好的解决方法。文中首先研究了互操作性的概念,实现主面向对象方法对互操作性的支持机制;在对ＤＣＥ机制和ＣＯＲＢＡ的ＯＲＢ机制比较的基础上,采用面向对象方法和技术,开展了基于Ａｇｅｎｔ的分布客户／服务器集成框架的研究,提出了一种基于Ａｇｅｎｔ的分布式通用框架,以支持客户／服务器应用的开发和实现     

多Agent协同工作环境MACE

在ＣＡＤ／ＣＡＭ和ＣＩＭＳ等领域的分布协同计算中,分布人工智能领域的多Ａｇｅｎｔ技术已逐步得到越来越多的应用,本文阐述了ＭＡＣＥ（Ｍｕｌｔｉ－ＡｇｅｎｔＣｏｏｐｅｒａｔｉｖｅＥｎｖｉｒｏｎｍｅｎｔ）多Ａｇｅｎｔ协同工作环境中有关Ａｇｎｅｔ的概念,分类和结构,多Ａｇｅｎｔ系统结构,人与人交互界面,公用语言以及运行模式等问题,最后,以一个简单的机械组合件的交互和自动两种方式修改参数的协同设计为实例,论     

多智能体系统支撑环境MAS/TH-5

ＭＡＳ／ＴＨ－５系统是具有一定开放性的支持ＭＡＳ构造与集成的支撑环境,它将开发与运行环境集为一体,形成整体解决方案．同时,文中所构造的具有实际应用价值的Ａｇｅｎｔ模型,为支撑环境提供了理论和技术基础．这种模型具有理性平衡的特点．该模型还为用户提供了建立其他Ａｇｅｎｔ模型的一般性框架,可以满足ＭＡＳ系统中Ａｇｅｎｔ交互的需求．在支撑环境上,文中所设计的Ａｇｅｎｔ语言具有描述ＢＤＩ等思维状态的能力,可处理较复杂的实际应用问题．     

面向Agent计算(AOC)原理

Ａｇｅｎｔ的出现使我们看到了ＡＩ进一步发展的希望,由于对Ａｇｅｎｔ缺乏统一的认识,使得在设计Ａｇｅｎｔ系统时出现一些混乱,我们认为造成这一状况的根本原因在于设计者对面向Ａｇｅｎｔ计算原理认识有偏差,本文将智能划分三个层次,并从知识层次和行为层次阐述ＡＯＣ基本原理。     

基于主控流动的多级Multi-Agent系统

从分析人的思维活动着手,提出了模拟人类智能活动过程构筑Ｍｕｌｔｉ－Ａｇｅｎｔ系统的方法,并由该方法构造了基于主控流动的多级Ｍｕｌｔｉ－Ａｇｅｎｔ系统。其主要特点是把小 Ｍｕｌｔｉ－Ａｇｅｎｔ系统视为一个特殊的Ａｇｅｎｔ,并由这种特殊的Ａｇｅｎｔ组成更高一级的Ａｇｅｎｔ系统…从而形成多级Ｍｕｌｔｉ－Ａｇｅｎｔ系统,而且在每一级Ａｇｅｎｔ系统中均采用了主控流动策略,使得整个系统能够把巨量的Ａｇｅｎｔ有效地结合起来。系统效率高,能主动改变和适应环境,为设计具体的大规模Ｍｕｌｔｉ－Ａｇｅｎｔ系统提供了一种可行的解决方案。     

基于组织干部人事管理领域的构件库管理系统

近年来,我国各级政府部门对组织干部人事管理系统的需求与日俱增。为了应对大量的系统开发需求,希望通过对组织干部人事管理领域的分析,设计生产出基于组织干部人事管理领域的软件构件,并进行构件的管理与组装,最终快速生成用户期望的组织干部人事管理系统。为了解决当前通用构件库无法适应组织干部人事管理领域需求的问题,设计建立了基于组织干部人事管理领域的构件库管理系统。文中分析了领域工程以及软件构件库的研究方法,根据组织干部人事管理领域的领域特性,建立起一套专有的构件库管理系统。     

多Agent系统中软构件的动态绑定机制及其操作语义

近年来,越来越多的以计算机网络为平台的应用系统表现出自主性、动态性、开放性和异构性的特点,这使得软件开发理论和技术需要从软件体系结构的角度对这类系统的开发提供支持.面向Agent的软件开发技术提供了高层和自然的抽象方式对软件系统进行分析和设计,但现有面向Agent的方法学将Agent Class或者Agent Type视为多Agent系统软件体系结构的软构件,与Agent之间的关系仅仅是实例化的关系,这难以满足复杂系统对动态性的需求.从软件体系结构的角度上分析了多Agent系统中软构件的形式和机制,将Caste作为软构件,并以此为基础提出了Caste与Agent之间的动态绑定关系,定义了支持该机制的4个基本操作:join,quit,activate和inactivate及其操作语义,用以来指导多Agent系统软件体系结构的设计和实现.     

基于Agent的分布式构件库系统体系结构

在分析了构件库及其复用现状的基础上,引入Agent技术,提出了一个基于Agent的分布式构件库系统,给出了体系结构.该系统通过多Agent之间的相互协作,能较好地满足在各企业间跨越构件库请求并检索构件的需求.     

Linking GIS and water resources management models: an object-oriented method

Many challenges are associated with the integration of geographic information systems (GISs) with models in specific applications. One of them is adapting models to the environment of GISs. Unique aspects of water resource management problems require a special approach to development of GIS data structures. Expanded development of GIS applications for handling water resources management analysis can be assisted by use of an object oriented approach. In this paper, we model a river basin water allocation problem as a collection of spatial and thematic objects. A conceptual GIS data model is formulated to integrate the physical and logical components of the modeling problem into an operational framework, based on which, extended GIS functions are developed to implement a tight linkage between the GIS and the water resources management model. Through the object-oriented approach, data, models and users interfaces are integrated in the GIS environment, creating great flexibility for modeling and analysis. The concept and methodology described in this paper is also applicable to connecting GIS with models in other fields that have a spatial dimension and hence to which GIS can provide a powerful additional component of the modeler’s tool kit.     

Modelling the GSM Handover Protocol in CommUnity

CommUnity is a formal approach to software architecture. It has a precise, yet intuitive mathematical semantics based on category theory. It supports, at the methodological level, a clear separation between computation, coordination, and distribution (including mobility). It provides a simple state-based language for describing component behaviour that is inspired by Unity and Interacting Processes. It also addresses composition as a first class concern and accounts for the emergence of global system properties from interconnections. This paper describes the approach and available tool support by modelling essential aspects of the GSM handover protocol. We also sketch a framework that we are implementing for the distributed execution of such specifications using Klava, a Java library for mobile agent systems based on tuple spaces.     

KEMNAD: A KNOWLEDGE ENGINEERING METHODOLOGY FOR NEGOTIATING AGENT DEVELOPMENT

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardized components rather than reinventing the wheel each time. Moreover, because these patterns are identified from a wide variety of existing negotiating agents (especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system.     

智能主体在构件库系统中的应用研究

基于构件的软件开发(CBSD)能有效地提高软件的开发效率,提高软件的质量,降低开发和维护成本,因此它成为软件工程的研究热点之一.构件库是CBSD的核心技术之一,在分布式构件库系统中,通过多智能主体之间的相互协作,能较好地满足在各企业间跨越构件库请求并检索构件的需求.给出了一个基于多智能主体的分布式构件系统体系结构,详细讨论了其中的检索主体、请求主体和发布主体.     

An embeddable mobile agent platform supporting runtime code mobility,interaction and coordination of mobile agents and host systems

Agent technology is emerging as an important concept for the development of distributed complex systems. A number of mobile agent systems have been developed in the last decade. However, most of them were developed to support only Java mobile agents. In order to provide distributed applications with code mobility, this article presents a library, the Mobile-C library, that allows a mobile agent platform, Mobile-C, to be embeddable in an application to support mobile C/C++ codes carried by mobile agents. Mobile-C uses a C/C++ interpreter as its Agent Execution Engine (AEE). Through the Mobile-C library, Mobile-C can be embedded into an application to support mobile C/C++ codes carried by mobile agents. Using mobile C/C++ codes, it is easy to interface a variety of low-level hardware devices and legacy systems. Through the Mobile-C library, Mobile-C can run on heterogeneous platforms with various operating systems. The Mobile-C library has a small footprint to meet the stringent memory capacity for applications in mechatronic and embedded systems. The Mobile-C library contains different categories of Application Programming Interfaces (APIs) in both binary and agent spaces to facilitate the design of mobile agent based applications. In addition, a rich set of existing APIs for the C/C++ interpreter employed as the AEE allows an application to have complete information and control over the mobile C/C++ codes residing in Mobile-C. With the synchronization mechanism provided by the Mobile-C library for both binary and agent spaces, simultaneous processes across both spaces can be coordinated to get correct runtime order and avoid unexpected race condition. The study of performance comparisons indicates that Mobile-C is about two times faster than JADE in agent migration. The application of the Mobile-C library is illustrated by dynamic runtime control of a mobile robot’s behavior using mobile agents.     

Knowledge-Based System Explanation: The Ripple-Down Rules Alternative

The ability to provide explanations has been seen as a key feature of expert systems (ES) typically not offered by other types ofcomputer systems. ES need to offer explanations because ofimprecise domains and the use ofheuristics. Verification is not enough. ES need to justify and be accountable. Explanation is seen as an important activity for knowledge-based systems as it satisfies the user's need to decide whether to accept or reject a recommendation. In this paper we review explanation in first-generation and second-generation ES. An alternative is offered to the main approaches which uses multiple classification ripple-down rules and challenges even the goals of explanation. Instead of trying to give explanations which provide a meaningful line of reasoning and which are tailored to suit the individual it may be just as useful to provide the user with sufficient information and browsing tools to develop their own line of reasoning. The type of information that can assist understanding is the context in which the recommendation applies (which is provided through the display ofrelevant cases and exception rule history) and the ability to explore an abstraction hierarchy of the rules using formal concept analysis. An explanation tool kit aimed at putting the user in control is described and evaluated in this paper. Received 15 January 2001 / Revised 21 June 2001 / Accepted in revised form 1 October 2001     

A Novel Bayes Model: Hidden Naive Bayes

Because learning an optimal Bayesian network classifier is an NP-hard problem, learning-improved naive Bayes has attracted much attention from researchers. In this paper, we summarize the existing improved algorithms and propose a novel Bayes model: hidden naive Bayes (HNB). In HNB, a hidden parent is created for each attribute which combines the influences from all other attributes. We experimentally test HNB in terms of classification accuracy, using the 36 UCI data sets selected by Weka, and compare it to naive Bayes (NB), selective Bayesian classifiers (SBC), naive Bayes tree (NBTree), tree-augmented naive Bayes (TAN), and averaged one-dependence estimators (AODE). The experimental results show that HNB significantly outperforms NB, SBC, NBTree, TAN, and AODE. In many data mining applications, an accurate class probability estimation and ranking are also desirable. We study the class probability estimation and ranking performance, measured by conditional log likelihood (CLL) and the area under the ROC curve (AUC), respectively, of naive Bayes and its improved models, such as SBC, NBTree, TAN, and AODE, and then compare HNB to them in terms of CLL and AUC. Our experiments show that HNB also significantly outperforms all of them.