基于多Agent技术的分布式协同设计结构的研究

将多Agent技术引入协同设计中，使所构造的协同设计系统具有多Agent系统的分布性、协作性、智能性的特点。文中给出了Agent的结构、协同设计单元的多Agent组成和基于Web服务的整个协同设计系统的结构； 并对协同设计系统实现的一些关键技术进行了讨论，包括Agent的创建、Agent之间的交互、知识的共享和Agent之间的冲突的消解。     

基于多Agent的协同家具设计系统(CoFCADS)的研究

协同设计是实现并行工程的关键,CSCW为协同设计的实现提供了有力的环境和技术支持。本文简要介绍了Agent单元和多Agent系统的概念和特性,介绍了协同家具设计系统的Agent单元结构,提出了一个基于多Agent的协同家具设计系统模型,最后对基于多Agent的家具协同设计系统的两种实现模式进行了阐述。重庆大学机械工程学院 付红桥 何玉林     

MAS中基于Ontology的知识表示与推理研究

采用基于Ontology的知识表示方法,解决多Agent的知识表示和共享问题,实现知识的自动推理和获取,实现多Agent之间语义理解,体现Agent的智能特征.在多Agent原型旅游系统中,采用OWL描述Ontology定义相关领域的知识表示与推理,为Agent之间的学习、协商,进一步交互通信打下基础.     

基于多Agent的协同家具设计系统（CoFCADS）的研究

协同设计是实现并行工程的关键，CSCW为协同设计的实现提供了有力的环境和技术支持，本文简要介绍了Agent单元和多Agent系统的概念和特性，介绍了协同家具设计系统的Agent单元结构，提出了一个基于多Agent的协同家具设计系统模型，最后对基于多Agent的家具协同设计系统的两种实现模式进行了阐述。     

基于协同多Agent的智能化产生式CAPP系统框架

该文提出的协同多Agent产生式系统,将一个复杂的工艺设计问题分解成几个简单的问题,分别采用Agent进行解决,各个Agent具有独自的知识和推理结构,在协同的机理下组合成一个有机的系统。采用多Agent协同结构的智能化产生式CAPP系统能够有效地解决产生式系统的灵活性、智能化、协同化和虚拟化,并能够不断地产生新的知识和方法,并加以保存。该文提出的采用多Agent协同结构的智能化产生式CAPP系统框架及其运行机制,能够在实践中发挥较大的作用,有助于产生新的产生式CAPP系统。     

基于Multi-agent的分布式电梯故障诊断系统的研究

采用基于分布式人工智能的思想,将多Agent技术引入电梯故障诊断领域,分析了基于MAS的分布式智能故障诊断方法和过程;研究讨论了基于MAS的分布式智能故障诊断系统中Agent之间的调度协同求解方法和机制;给出了知识共享与重用的方法;建立了一种分布式多Agent诊断系统结构及其原型系统;通过在电梯故障诊断的应用仿真,提高了故障诊断的实时性、准确性和整体性能。     

基于多Agent的政府知识管理系统模型研究

针对现有政府知识管理系统的局限性和政府知识管理的复杂性,采用面向多Agent的系统设计方法,设计了一个基于多Agent的政府知识管理系统模型,给出了系统模型实现的一些关键技术.该模型由多个Agent来协同实现政府知识的异构整合、知识推送、知识利用等服务,以满足政务知识管理的异构知识集成、智能化决策、个性化服务等实际需求.     

用倾向最大回报的协同进化优化多Agent合作

进化计算是多Agent系统学习的一个有用技术。在多Agent系统研究中的某些领域,一种常用的方法是协同进化多Agent合作。研究已经指出:在某些领域,协同进化系统更倾向于稳定而不是成效(即收敛到局部优化解)。这与多Agent系统研究的目的(追求利益最大化)是不相符的。为此,文章提出了一种基于混沌机制的倾向于最大回报的协同进化算法,改进了Wiegand等人的工作,。理论分析和仿真实验表明,这种基于混沌机制的倾向能促使协同进化向更优化的全局稳定点收敛,从而帮助协同进化算法在某些合作的多Agent领域发现更好的解(甚至是最优解)。     

基于多Agent系统的自调节及协同工作的组合投资模型

Agent技术特别是多Agent系统（MAS,Multi-Agent System）为解决人工智能等领域复杂问题提供了一个新途径,多Agent系统重点研究如何协调系统中的各个Agent的行为使其协同工作。针对多阶段组合投资问题,提出了一个基于多Agent系统的自调节及协同工作的组合投资策略模型。该模型系统中的各个Agent通过通讯共享知识,在求解问题的搜索空间中进行协同搜索,在更短的搜索步长内得到问题的解,极大地提高了系统性能。该模型具有不基于任何股票模型、时间复杂度低以及逼近最优投资策略速度较快等优点,实验证明具有一定的实际意义。     

基于多Agent系统的自调节及协同工作的组合投资模型

Agent技术特别是多Agent系统(MAS,Multi-Agent System)为解决人工智能等领域复杂问题提供了一个新途径,多Agent系统重点研究如何协调系统中的各个Agent的行为使其协同工作.针对多阶段组合投资问题,提出了一个基于多Agent系统的自调节及协同工作的组合投资策略模型.该模型系统中的各个Agent通过通讯共享知识,在求解问题的搜索空间中进行协同搜索,在更短的搜索步长内得到问题的解,极大地提高了系统性能.该模型具有不基于任何股票模型、时间复杂度低以及逼近最优投资策略速度较快等优点,实验证明具有一定的实际意义.     

Knowledge management of product design: A requirements-oriented knowledge management framework based on Kansei engineering and knowledge map

For the knowledge management of product design, knowledge innovation is the foundation and motivation for the independent innovation and enhancing the core competitiveness. Most of the product knowledge exists in the brain of designers. How to obtain the required knowledge accurately in massive knowledge database becomes the key to knowledge innovation. However, the design knowledge based on consumer’s requirement has not been extensively studied. There is no consensus on the reasonable and effective implementation of the knowledge management framework to select the optimum design knowledge based on the consumer’s requirements. In this study, to efficiently realize the knowledge acquisition and knowledge selection, a requirements-oriented knowledge management model is established, with the advantage of Kansei engineering in knowledge acquisition and multi-objective decision-making in knowledge selection. Finally, the outdoor leisure chairs design is used as a case study to explain the implementation of the knowledge management framework. To reveal the advantages of the framework, it was compared with other frameworks. The results show that the proposed knowledge management framework is more efficient and provided a method of designers to acquire design knowledge based on the consumer’s requirements.     

铁路动车组故障诊断知识库管理系统的设计

针对我国动车组维修的特点,为动车组维修人员能够及时、快速地对动车组发生的故障进行分析和处理,运用人工智能的思想,结合数据库技术,设计了一套知识表示和知识库管理系统,对动车组故障信息及其原因信息、处理措施信息进行维护,处理了知识的正确性、完备性、冗余性、一致性检验,并在一定程度上实现了知识处理的自动化,对我国高速铁路动车组维修工作起到辅助支持作用．有很强的实际意义。     

An ontology-based knowledge framework for engineering material selection

Engineering material selection intensively depends on domain knowledge. In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection.     

铁路动车组故障诊断知识库管理系统的设计

针对我国动车组维修的特点,为动车组维修人员能够及时、快速地对动车组发生的故障进行分析和处理,运用人工智能的思想,结合数据库技术,设计了一套知识表示和知识库管理系统,对动车组故障信息及其原因信息、处理措施信息进行维护,处理了知识的正确性、完备性、冗余性、一致性检验,并在一定程度上实现了知识处理的自动化,对我国高速铁路动车组维修工作起到辅助支持作用,有很强的实际意义。     

Updating knowledge bases

We consider the problem of updating a knowledge base, where a knowledge base is realised as a normal (logic) program. We present procedures for deleting an atom from a normal program and inserting an atom into a normal program, concentrating particularly on the case when negative literals appear in the bodies of program clauses. We also prove various properties of the procedures including their correctness.     

一种通用的智能化可视框架

为经推理过程产生的影像提供了一种通用的可视化框架,这一框架与以往采用的方法有很大的区别：可视化系统将从一个基于外部数据源的知识库中取回可视信息,从而能够满足用户的不同可视化需求。这一知识库由用户以逻辑语言编写,主要包括关于可视目标、它们的相互关系以及其几何视觉特征的描述。此外详细介绍了知识的表达方式,同时运用一个简单的实例来对其智能可视化进行说明。     

KDD中知识库智能接口的设计与实现

文章利用面向对象的编程技术,采用Delphi5.0语言,针对由不同数据库系统构成的知识库系统,实现了不同知识库系统的无缝连接,较好地解决了不同知识库系统的接口问题,为KDD中不一致知识的的通用处理奠定了坚实的基础。     

Updating knowledge bases II

We consider the problem of updating a knowledge base, where a knowledge base is realised as a (logic) program. In a previous paper, we presented procedures for deleting an atom from a normal program and inserting an atom into a normal program, concentrating particularly on the case when negative literals appear in the bodies of program clauses. We also proved various properties of the procedures including their correctness. Here we present mutually recursive versions of the update procedures and prove their correctness and other properties. We then generalise the procedures so that we can update an (arbitrary) program with an (arbitrary) formula. The correctness of the update procedures for programs is also proved.     

An automatic literature knowledge graph and reasoning network modeling framework based on ontology and natural language processing

With the advancement of scientific and engineering research, a huge number of academic literature are accumulated. Manually reviewing the existing literature is the main way to explore embedded knowledge, and the process is quite time-consuming and labor intensive. As the quantity of literature is increasing exponentially, it would be more difficult to cover all aspects of the literature using the traditional manual review approach. To overcome this drawback, bibliometric analysis is used to analyze the current situation and trend of a specific research field. In the bibliometric analysis, only a few key phrases (e.g., authors, publishers, journals, and citations) are usually used as the inputs for analysis. Information other than those phrases is not extracted for analysis, while that neglected information (e.g., abstract) might provide more detailed knowledge in the article. To tackle with this problem, this study proposed an automatic literature knowledge graph and reasoning network modeling framework based on ontology and Natural Language Processing (NLP), to facilitate the efficient knowledge exploration from literature abstract. In this framework, a representation ontology is proposed to characterize the literature abstract data into four knowledge elements (background, objectives, solutions, and findings), and NLP technology is used to extract the ontology instances from the abstract automatically. Based on the representation ontology, a four-space integrated knowledge graph is built using NLP technology. Then, reasoning network is generated according to the reasoning mechanism defined in the proposed ontology model. To validate the proposed framework, a case study is conducted to analyze the literature in the field of construction management. The case study proves that the proposed ontology model can be used to represent the knowledge embedded in the literatures’ abstracts, and the ontology elements can be automatically extracted by NLP models. The proposed framework can be an enhancement for the bibliometric analysis to explore more knowledge from the literature.     

一个适于CAI课件设计的超文本知识库结构模型

目前在CAI课件设计中最受推崇的知识组织形式就是超文本结构.本文在Dexter超文本参考模型的基础上,针对CAI课件设计中的特殊需要,提出一种超文本知识库结构模型.