分布式黑板模型的设计与实现

由于传统的黑板模型是基于串行硬件环境之上的，因此其效率和可靠性受到极大限制，使以此模型为结构的很多专家系统无法实用化。为了解决这个问题，我们基于Ｎｏｖｅｌｌ网络环境，研制了一种分布式黑板模型。本文介绍了这个模型的体系结构，描述了系统所采用的一些技术。     

分布式图板模型的设计与实现

由于传统的黑板模型是于串行硬件环境之上的，因此其效率和可靠性受到极大限制，使以此模型为结构的很多专家系统无法实用化。为了解决这个问题，我们基一地Ｎｏｖｅｌｌ网络环境，研制了一种分布式黑板模型。本文介绍了这个模型的体系结构，描述了系统所采用的一些技术。     

分布式黑板模型的设计

由于传统的黑板模型是基于串行硬件环境之上的,因此其效率和可靠性受到极大限制,使以此模型为结构的很多专家系统无法实用化。为了解决这个问题,该文设计了一种分布式黑板模型,描述了采用的一些技术。     

基于面向对象黑板模型的防空作战专家系统研究

本文在分析了防空作战专家系统功能和领域知识类型的基础上，将面向对象方法和问题求解的黑板模型有机结合，提出了一种基于面向对象黑板模型的防空作战专家系统。该系统通过改善黑板模型的控制方式．提高了知识处理的并发性，同时引入消息管理器机制实现了知识的实时处理。     

应用于控制领域的黑板结构

本文主要研究智能控制系统的框架结构问题。首先总结了黑板模型的两个本质特征,然后分析了控制领域问题求解的特点及其对黑板模型的适用性。在此基础上,提出一种能使控制领域的问题求解与控制作用相结合的黑板结构,并给出了一个基于该结构的应用实例。     

多路传感器数据融合系统的FOOB设计方法

本文综合功能分解、面向对象分析和黑板模型给出一个多路传感器数据融合系统的设计方法－ＦＯＯＢ。使系统的设计和开发者把问题求解分成模块、对象、知识源或进程；利用黑板模型使整个系统设计减少开销，增强可靠性；使系统具有复用性和可扩展性。     

渗碳专家系统中的多专家求解问题的研究

本文研究了在渗碳专家系统中的问题求解策略，为了避免系统求解的主观性和片面性，提出了多黑板系统，例如问题黑板，辩论择优黑板，领域黑板和结论黑板作为问题的求解策略。使其非公认的渗碳领域问题通过专家进行辩论择优选出最佳解，为此提出建立基于多元组命题性知识的辩论理论框架，并体现不同策略的辩论算法，对此进行了计算机仿真，结果证明此方法是有效的。     

面向对象的黑板模型

引入了面向对象程序设计思想，阐述了面向对象的黑板模型，并把知识源表示成对象，使它不仅具有问题求解能力，还具有接收消息和发送消息的能力，使集中控制变为分散控制，改善了传统黑板模型的不足。     

寿命服从多元指数分布的树型网格服务可靠性与性能模型

已有网格服务可靠性与性能模型均假设资源节点和链路可靠性服从独立指数分布,这种假设有利于简化建模和分析,但同时也限制了已有模型的应用范围,因为在实际网格环境中,资源节点和链路可靠性存在相关性,即寿命服从多元指数分布.针对这个问题,在已有的树型网格服务模型的基础上,把资源节点和链路的寿命分布从一元指数分布拓展到多元指数分布,提出一种寿命服从多元指数分布的树型网格服务可靠性与性能模型,同时给出该模型的求解算法.寿命服从多元指数分布的树型网格服务可靠性与性能模型求解算法通过构造互斥分解树,把模型求解问题分解成互斥极小项来获得模型的解.实例和理论对比分析表明:寿命服从多元指数分布的树型网格服务可靠性与性能模型不仅兼容已有树型网格服务模型,而且能够适用于寿命服从多元指数分布的树型网格服务计算环境建模,同时寿命服从多元指数分布的树型网格服务可靠性与性能模型求解算法不仅能更有效求解已有树型网格服务模型, 而且可以求解更复杂的多元指数分布树型网格服务模型,与已有网格服务模型求解算法相比具有更强 的通用性和更高的算法效率.     

基于浅层知识和深层知识推理的故障诊断专家系统工具

以专家系统和诊断问题求解为基础，建立了基于浅层知识和深层知识推理相结合的故障诊断专家系统工具。文中论述了工具的结构、知识表示、参数设计、推理机制、黑板控制、学习机制和其它支持环境。     

A blackboard system for the off-line programming of Robots

This paper describes the use of the blackboard architecture for the off-line programming of an IMB 7565 Robot. A blackboard system was implemented in PROLOG and it has been applied successfully for the automatic generation of a control code for the robot to perform the task of block assembly in an environment with an obstacle. The opportunistic type of problem-solving offered by the blackboard architecture has succeeded in obtaining a solution. The user-interface to the system is represented as a knowledge source in the blackboard system, which allows the user to modify the goal specifications during the operation of the blackboard system.     

Design and analysis techniques for concurrent blackboard systems

This paper gives a formal model for blackboard systems that provides a consistent method for describing a blackboard system. The formal model describes the basic components of a blackboard system and how the components interact. A set of blackboard system design tools has been developed and validated for implementing systems that are expressed using the formal model. The tools are used to test and refine a proposed blackboard system design before the design is implemented. The set of blackboard system design tools consists of a knowledge source organizer, a knowledge source input/output connectivity analyzer, a validated blackboard system simulation model, and a blackboard system code generator. The lack of design and analysis tools has hindered the full realization of the concurrency inherent in the blackboard problem-solving model. Use of a centralized control mechanism and knowledge source contention in accessing the blackboard have restricted the concurrency possible in previous systems. Using the design, simulation, and analysis tools, a fast, efficient, and powerful concurrent object-oriented blackboard system has been developed     

Blackboard systems

The blackboard architecture is becoming an increasingly popular basis for the construction of problem-solving systems which operate in domains requiring qualitatively different kinds of knowledge to be applied in order to arrive at a solution to a problem. This paper presents the metaphor on which blackboard systems are based. The metaphor is then given an interpretation which constitutes the blackboard architecture. The structure of the blackboard database and its contents are considered from an evolutionary point of view. Finally, the paper considers some of the alternative approaches to the control of problem-solving in blackboard systems.     

Development of an object-oriented blackboard model for stamping process planning in progressive die design

This paper reports preliminary work to investigate the suitability of using a blackboard framework as a problem-solving model for stamping process planning in progressive die design. The model is described at two levels: knowledge level and computational level. The knowledge level describes how the stamping process planning domain is represented in a blackboard architecture. The computational level describes how the blackboard architecture is modeled and implemented using object technology. A software prototype has been developed using CLIPS and C++ interfaced with Solid Edge CAD system. An example is presented to illustrate the feasibility and practicality of the proposed approach.     

A behaviour-based architecture with attention control

In this paper we present a behaviour-based mobile robot system for task execution. The behaviour model of this system consists of a number of motion behaviours, including reflexes and voluntary motion behaviours, and knowledge acquisition modules providing supporting information. Execution of a task is regarded as a problem-solving process. A blackboard model is introduced to overcome some shortcomings of the behaviour-based architectures, especially concerning modularity and task execution capability. The concept of attention is introduced in the behaviour control, which is more advantageous than the behaviour control mechanisms presented in the literature. Its introduction results in situation-dependent behaviour coordination. For efficient task execution, environment knowledge is maintained in a memory. Task-achieving behaviour is designed to make use of the memory when available.     

地质分析专家系统GAES的设计

地质分析是一项复杂的人类劳动,采用人工智能技术模拟人类专家活动,可以大大减轻人类的负担.因此,开发了一个地质分析专家系统GAES.该系统以黑板模型为基础,采用分布式系统结构,在中心节点的协调控制下,各普通节点相互合作,共同进行问题求解.在系统技术特点方面,解决了知识源分配、冲突消解和知识源筛选等问题,该系统具有求解效率高、可靠性强、通讯机制好等特点.     

A blackboard architecture for control

The control problem—which of its potential actions should an AI system perform at each point in the problem-solving process?—is fundamental to all cognitive processes. This paper proposes eight behavioral goals for intelligent control and a ‘blackboard control architecture’ to achieve them. The architecture distinguishes domain and control problems, knowledge, and solutions. It enables AI systems to operate upon their own knowledge and behavior and to adapt to unanticipated problem-solving situations. The paper shows how opm, a blackboard control system for multiple-task planning, exploits these capabilities. It also shows how the architecture would replicate the control behavior of hearsay-ii and hasp. The paper contrasts the blackboard control architecture with three alternatives and shows how it continues an evolutionary progression of control architectures. The paper concludes with a summary of the blackboard control architecture's strengths and weaknesses.     

A blackboard application for process monitoring and supervision

This paper describes the architecture of a supervisory control and data-acquisition system. It works like an operator support tool by diagnosing malfunctions of a production process and inspecting the quality of the product. The system provides the operator in a plant with relevant process data and, at the same time, has to meet tough real-time requirements. The integration of intelligent alarm processing into a large supervisory control system will be described and techniques covering on-line processing of real-time data and intelligent alarm processing will be discussed. The system is based on a blackboard architecture which integrates a sequence of problem-solving methods and exhibits an incremental and opportunistic problem-solving style.