Kave: a tool for knowledge acquisition to support artificial ventilation

A decision support system for artificial ventilation is being developed. One of the fundamental goals for this system is the application of the system when a domain expert is not present. Such a system requires a rich knowledge base. The knowledge acquisition process is often considered to be the bottleneck in acquiring such a complete knowledge base. Since no single available method, for example interviewing domain experts, is sufficient for removing this bottleneck, we have chosen a combination of different methods. The different backgrounds of knowledge engineers and domain experts could cause communication restrictions and difficulties between them, e.g. they might not understand each others knowledge domain and this will affect formulation of the knowledge. To solve this problem we needed a tool which supports both the knowledge engineer and the domain expert already from the initial phase of developing the knowledge base. We have developed a knowledge acquisition system called KAVE to elicit knowledge from domain experts and storing it in the knowledge base. KAVE is based on a domain specific conceptual model which is a result of cooperation between knowledge engineers and domain experts during identification, design and structuring of knowledge for this domain. KAVE includes a patient simulator to help validate knowledge in the knowledge base and a knowledge editor to facilitate refinement and maintenance of the knowledge base.     

Knowledge representation in MICKEY: an expert system for designingmicroprocessor-based systems

This paper presents the knowledge representation schemes adopted in MICKEY, a knowledge based system for designing microprocessor based systems. MICKEY is essentially a hybrid expert system, using rules and procedures for achieving the different design tasks. We briefly describe the hierarchy of tasks in this problem domain, and emphasize on the refinement paradigm, constraint propagation, conflict resolution and task management strategies adopted in MICKEY. Next, we dwell upon the different knowledge sources and their functions, with respect to the particular design domain. Finally, we present an industrial design, achieved by MICKEY, to demonstrate its applicability     

基于模糊评判的Web服务评价模型

Web服务质量的评价是指导Web服务的选取与组合的主要手段,而目前的Web服务评价模型采用通用的服务评价属性作为评价因子,忽略了Web服务质量评价的多元性和模糊性。用基于模糊理论的方法描述Web服务评价模型,支持使用专业人员或领域专家的领域知识计算评价因子的权值分布。与其它Web服务评价机制相比较,该模型能更加准确、客观地反映实际情况,减少人为的主观随意性,对Web服务质量做出了合理的评价。     

Intentional learning agent architecture

Dealing with changing situations is a major issue in building agent systems. When the time is limited, knowledge is unreliable, and resources are scarce, the issue becomes more challenging. The BDI (Belief-Desire-Intention) agent architecture provides a model for building agents that addresses that issue. The model can be used to build intentional agents that are able to reason based on explicit mental attitudes, while behaving reactively in changing circumstances. However, despite the reactive and deliberative features, a classical BDI agent is not capable of learning. Plans as recipes that guide the activities of the agent are assumed to be static. In this paper, an architecture for an intentional learning agent is presented. The architecture is an extension of the BDI architecture in which the learning process is explicitly described as plans. Learning plans are meta-level plans which allow the agent to introspectively monitor its mental states and update other plans at run time. In order to acquire the intricate structure of a plan, a process pattern called manipulative abduction is encoded as a learning plan. This work advances the state of the art by combining the strengths of learning and BDI agent frameworks in a rich language for describing deliberation processes and reactive execution. It enables domain experts to specify learning processes and strategies explicitly, while allowing the agent to benefit from procedural domain knowledge expressed in plans.     

Negotiation in a knowledge-based concurrent engineering design environment

Abstract: Computational support for concurrent engineering design presents a number of issues in the design of knowledge-based systems. A fundamental concern is the need to provide the life-cycle perspective in recommending design alternatives. It is argued that such a complex knowledge-based system should be distributed, due to the inherent problems with large knowledge bases and the maintenance of consistency. Inconsistent local views of a problem and different priorities on design issues are expected between different knowledge-based design perspectives. These inconsistencies and different priorities will lead inherently to conflict which has to be resolved. This paper addresses the issues and key variables in conflict resolution and presents a strategy that can be applied for managing the conflict resolution process. We propose negotiation as the method of analysing a conflict situation, applying an appropriate conflict resolution strategy and monitoring its performance. We present an overview of the nature of conflict and some conflict resolution strategies, and see in what situations certain strategies are appropriate.     

Agent组织中的政策导向型协作模型

传统Agent协作模型强调Agent的高度自主性,其自发协作过程完全出于内部的"自私性"动机,难以在模型中表达宏观层面上的引导及系统外部的约束,在应用于开放复杂软件系统时,将面临可信度不能满足要求、计算复杂度高及没有有效的冲突消解机制这3方面的问题,这阻碍了Agent技术在现实软件系统建模中的应用.采用组织与政策隐喻,提出Agent组织中的政策导向型协作模型,通过组织与政策给予Agent以宏观上的引导与外部的控制,以增强系统的可信度;采用扩展的可废止逻辑框架,对这一协作过程建立一个具有线性计算复杂度的形式化理论;逻辑体系中内置的优先级方式为系统提供了有效的冲突消解机制.并证明了模型所具有的一致性及其他特性,最后通过一个实例对系统作出验证性说明.     

基于PERT图的冲突检测的研究

冲突是协同设计过程中一个不可避免的实际问题,产生的原因是协同设计环境下不同设计群体之间存在各个方面的差异性。基于以上原因,提出了一种冲突检测模型,并在此基础上提出了冲突的分类和基于PERT图的冲突检测算法,此方法通过组合不同设计者的设计方案PERT图找出他们之间存在的冲突问题,进而进行消解。最后通过实例验证此方法的有效性。     

A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators

Expert systems (ES) development technology has been used to build rural business applications in the past but these have usually been developed using traditional expert systems shells. This paper introduces a new architecture for the development of a design environment where the domain experts can build a knowledge base for target-specific ES for rural business operators. The system allows rural business operators to use their own knowledge in building their own, target-specific ES for tailored development to their own specific requirements. At this stage, this reusable design environment caters for the Australian dairy industry but in the long run we claim it will be useful for the other livestock based rural industries such as beef cattle and sheep. This approach of developing target-specific ES contributes new knowledge in that it provides a new way of developing decision support by allowing human domain experts to develop relevant ES for different livestock farming business.An evolutionary prototyping approach was employed for initial development of a proof of concept example and as a method of outlining the solution environment. Multiple qualitative data collection methods were engaged to facilitate knowledge acquisition in the domain of milk protein enhancement for dairy operations. This paper also describes the generic development procedure used in this project.     

A smart conflict resolution model using multi-layer knowledge graph for conceptual design

Reducing the impact of conflicts on requirement-function-structure mapping in the early stage of product design is an important measure to achieve conceptual innovation, which relies on accurate reasoning of multi-domain knowledge. As product requirements become more personalized and diverse, traditional discrete knowledge organization and reasoning methods are difficult to adapt to the challenges of continuity and precision in conceptual solution. Knowledge graphs with complex networks have obvious advantages in association detection, knowledge visualization, and explainable reasoning of implicit knowledge, which offer innovative opportunities for conflict resolution in conceptual design. Therefore, a smart conflict resolution model using a multi-layer Knowledge Graph for Conceptual Design(mKGCD) is proposed in this study. A knowledge expression form of FBS-oriented design patent vocabulary is proposed, which is used for knowledge entity recognition and relation extraction based on natural language processing. A label mapping method based on inventive principles is used for patent classification and a four-layer semantic network for conflict resolution is constructed. Through semantic distance calculation, the designer's requirements for function/behavior/structure are smart deployed to obtain appropriate knowledge. A case study of the conceptual design of a collapsible installation and handling equipment demonstrates the feasibility of the proposed approach. The proposed method can not only meet the functional solution and innovation in the context of different design requirements, but also effectively improve the design efficiency in the iterative design process by means of multiple meanings of one graph.     

协同设计中多主体冲突问题的研究

从设计流程和体系结构的角度，对多主体冲突的产生、预防、检测与解决机制进行了系统的研究，提出了一个解决冲突问题的三层结构模型和各层相应的冲突解决策略，从而在控制级及领域级都对冲突进行了有效的避免和控制，该模型及方法在摩托车协同概念设计系统中得到了实现，为智能设计和协同设计奠定了基础。     

协同工作中冲突消解机制的研究

协同工作就是利用网络技术众多设计者共同合作完成任务,及时更新信息,保证网络信息的一致性与快速响应性。但是在协同工作过程设计成员自身条件差异,不可避免在协同设计中会产生冲突,所以准确及时对冲突检测与消解是协同工作的关键。因此提出一种新的集成化冲突消解模型,给出模型算法,利用模式匹配技术在这个模型中进行冲突检测与消解,采用克莫普匹配法进行冲突消解。通过实验证明,集成化模型和模式匹配技术很有效,对冲突检测准确,对冲突消解效率高,尤其处理大批量冲突时速度很快。效果非常显著,算法复杂度也很低。     

Business Processes Verification for e-Government Service Delivery

Domain experts knowledge represents a major source of information in the design and the development of user-centric and distributed service-based applications, such as those of e-government. Issues related both to the communication among domain and IT experts, and to the implementation of domain dependent requirements in service-based applications, have to be carefully considered to support both Public Administrations efficiency and citizen satisfaction. In this article, we provide as user-friendly approach toward business process assessment via formal verification. Starting from a semi-formal notation, well understood and largely used by domain experts, we provide a mapping to a formal specification in the form of a process algebra. This transformation makes possible formal and automatic verification of desired quality requirements. The approach has been already applied, with encouraging results, in the e-government domain to verify the quality of business processes related to the delivery of e-government digital services to citizens. Moreover, the approach is supported by a plug-in for the Eclipse platform permitting to have an integrated environment in which to design the process model and to assess its quality.     

Minimal Belief and Negation as Failure in Multi-Agent Systems

We propose an epistemic, nonmonotonic approach to the formalization of knowledge in a multi-agent setting. From the technical viewpoint, a family of nonmonotonic logics, based on Lifschitz's modal logic of minimal belief and negation as failure, is proposed, which allows for formalizing an agent which is able to reason about both its own knowledge and other agents' knowledge and ignorance. We define a reasoning method for such a logic and characterize the computational complexity of the major reasoning tasks in this formalism. From the practical perspective, we argue that our logical framework is well-suited for representing situations in which an agent cooperates in a team, and each agent is able to communicate his knowledge to other agents in the team. In such a case, in many situations the agent needs nonmonotonic abilities, in order to reason about such a situation based on his own knowledge and the other agents' knowledge and ignorance. Finally, we show the effectiveness of our framework in the robotic soccer application domain.     

一种以领域知识为中心的知识发现过程模型

针对知识发现在实际应用中的问题,提出了一种以领域知识为中心的知识发现过程模型,并将其形式化,描述了其动态语义。与已有的知识发现过程模型相比,此过程模型更能体现知识发现过程的本质特性,同时具有严格的形式化基础,为知识发现系统的设计和实际的知识发现应用提供了一个新的参考。     

基于描述逻辑的特征语义建模及验证

在软件产品线方法中,特征模型已被广泛用于获取领域需求以支持软件复用.但在一定程度上,各种方法对刻画特征模型以及特征之间约束关系存在语义上的冗余和混乱,不能有效对特征模型进行验证,也限制各种不同特征建模方法之间特征信息的共享.采用描述逻辑刻画了特征模型中的特征类、特征间关系与约束等方面,定义了特征间互斥、需要等约束的规则集合,用于对知识库中的语义特征模型实例进行一致性、完整性验证.并结合一个具体领域,对基于描述逻辑的特征建模及推理验证进行了详细论述.此研究对于领域特征模型的语义建模与验证、支持领域模型共享具有一定的指导作用.     

Distributed model‐independent consensus of Euler–Lagrange agents on directed networks

This paper proposes a distributed model‐independent algorithm to achieve leaderless consensus on a directed network where each fully‐actuated agent has self‐dynamics described by Euler–Lagrange equations of motion. Specifically, we aim to achieve consensus of the generalised coordinates with zero generalised velocity. We show that on a strongly connected graph, a model‐independent algorithm can achieve the consensus objective at an exponential rate if an upper bound on the initial conditions is known a priori. By model‐independent, we mean that each agent can execute the algorithm with no knowledge of the equations describing the self‐dynamics of any agent. For design of the control laws which achieve consensus, a control gain scalar and a control gain matrix are required to satisfy several inequalities involving bounds on the matrices of the agent dynamic model, bounds on the Laplacian matrix describing the network topology and the set of initial conditions; design of the algorithm therefore requires some knowledge on the bounds of the agent dynamical parameters. Because only bounds are required, the proposed algorithm offers robustness to uncertainty in the parameters of the multiagent system. We systematically show that additional relative velocity information improves the performance of the controller. Numerical simulations are provided to show the effectiveness of the algorithm. Copyright © 2016 John Wiley & Sons, Ltd.     

Expert systems: art alternative paradigm

There has recently been a significant effort by the A.I. community to interest industry in the potential of expert systems. However, this has resulted in far fewer substantial applications projects than might be expected. This article argues that this is because human experts are rarely required to perform the role that computer-based experts are programmed to adopt. Instead of being called in to answer well-defined problems, they are more of ten asked to assist other experts to extend and refine their understanding of a problem area at the junction of their two domains of knowledge. This more properly involves educational rather than problem-solving skills.An alternative approach to expert system design is proposed based upon guided discovery learning. The user is provided with a supportive environment for a particular class of problem, the system predominantly acting as an advisor rather than directing the interaction. The environment includes a database of domain knowledge, a set of procedures for its application to a concrete problem, and an intelligent machine-based advisor to judge the user's effectiveness and advise on strategy. The procedures focus upon the use of user generated “explanations” both to promote the application of domain knowledge and to expose understanding difficulties. Simple database PROLOG is being used as the subject material for the prototype system which is known as MINDPAD.