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。     

一种基于对象的黑板问题求解模型

为了提高黑板结构的效率,使并发问题求解得以进行.对传统的黑板结构进行了改进,引入面向对象技术,把知识源表示成对象,使它不仅具有问题求解能力,还具有接收和发送消息的能力,变集中控制为分散控制.最后以此模型为基础,实现了一个断层识别专家系统.实验结果表明,这种面向对象的黑板结构的思想是可行的,有一定的实用价值.     

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集中试验问题求解模型，因此其效率和可靠性受到很大限制，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，该模型具有可靠性高，求解速度快的特点。本文介绍了这个模型的体系结构，描述了系统采用的一些技术。     

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。     

黑板系统:问题求解的黑板模型及黑板结构的演变

第一个黑板系统是HEARSAY-Ⅱ口语理解系统(1971～1976)。随后,许多系统都采用了与HEARSAY-Ⅱ相似的系统结构,并且有类似的运行效果。本文旨在:(1)定义什么是“黑板系统”,(2)揭示黑板系统设计的丰富性和多样性。文章首先讨论所有黑板系统中都包含的基本概念—问题求解的黑板模型。为了使模型与实际系统相联系,介绍了基本的黑板模型的扩充——黑板框架结构,详细描述了模型的结构成分以及它们的功能。模型并不是天生的,它通常是许多实例的抽象。第二节回顾了“黑板系统”这一思想的产生和发展,并详细介绍了有助于形成黑板模型的一些应用系统的设计。文章的第二部分(刊登在THE AI MAGAZINE杂志的1986年八月刊上)描述了一些黑板系统,并作了对比,同时还讨论了适合于问题求解的黑板方法的应用问题的特征。     

基于Transputer网络的实时黑板模型试验床系统CPES

本文使用“黑板转播器”概念,在Ｔｒａｎｓｕｐｔｅｒ风格上实现了一个可用于实时领域的并行黑板模型试验床系统ＣＰＥＳ,它具有并行度高、模块化性能好的结构特点。本文对ＣＰＥＳ的性能如问题求解速度、并行状态下各项开销情况进行了测试,同时还对并行黑板模型的测试方法、性能衡量指标等进行了初步探讨;测试结果反映出ＣＰＥＳ具有较好的实时黑板模型试验床的性能和功能。     

黑板控制结构

控制问题——即在问题求解过程中,一个AI系统如何决定它要执行的动作——是每个智能系统都要解决的问题。本文介绍了智能控制应实现的八点行为目标及实现该目标的黑板控制结构。这种结构把控制问题当作一个实时规划问题,显式地加以解决,具有高度的灵活性。本文采用一个多任务规划的例子来帮助说明黑板控制结构中的一些概念。最后对黑板控制结构的长处与不足作了一个简略的总结。     

黑板结构在控制系统中的应用

本文介绍了黑板模型的基本原理,总结了黑板模型的特点,并把它应用于控制领域,与控制理论相结合,以具有典型工业对象特征的电加热炉为实际被控对象,构成一个专家控制系统。     

黑板结构在控制中的应用

本文介绍了黑板模型的基本原理，总结了黑板模型的特点，并把它应用于控制领域，与控制理论相结合，以具有典型工业对象特征的电加热炉为实际被控对象，构成一个专家控制系统。     

基于离散萤火虫算法的指控结构适应性调整

指挥控制组织结构的适应性调整是敏捷指控领域研究的热点问题。首先给出了指挥控制组织的基本组成要素,针对行动计划变化和战术决策实体失效两种战场突发事件,分析了这两种事件下的优化约束条件和优化目标,分别构建了指挥控制组织结构适应性调整问题的优化模型,设计了基于离散萤火虫算法的模型求解方法,给出了离散萤火虫算法的具体流程,最后通过具体算例对指控组织结构适应性调整模型和其求解算法进行了仿真验证和对比,仿真结果表明了求解方法的可行性和高效性。     

搅拌设备化工预设计专家系统的黑板系统结构

传统的手工设计混合设备的方法十分耗时且容易出错,因此实现设计的自动化和智能化是非常用意义的开发了搅拌设备化工预设计专家系统系统。详细介绍了专家系统的结构,系统采用两层黑板结构模型和多种知识源相结合的策略,来处理解决复杂的协同问题。知识源包括设计规则库、设计公式库和机械设备标准库,内部黑板主要是为规则库的推理机存储信息服务,而全局黑板系统则是整个系统的数据共享和信息交换中心,并采用层次框架结构进行表达,将人工智能技术与普通设计程序相结合,可以在设计过程为用户提供系统的帮助和指导,来实现搅拌设备设计的自动化和智能化。     

An object-oriented cooperative distributed problem solving shell with groupware management ability

In this paper, an Object-Oriented Cooperative Distributed Problem Solving Shell (OOCDPSS) with groupware management ability is designed. The groupware management facilities, which satisfy the needs of development and execution of the cooperative distributed problem solving activities, can reinforce concurrency and parallelism, accommodation and integration of heterogeneous, uncoordinated problem solvers cooperating on one common goal. This OOCDPSS system constructs the non-embedded groupware architecture by a hierarchy of leader agents. The leader agent that adopts a distributed blackboard control mechanism can assist the cooperating problem solvers with all the cooperative and coordinative activities at run time through a democratic, contract-net protocol. In this blackboard control mechanism, the system control unit and domain control unit are explicitly separated and put side-by-side in a simple control loop to simplify the control mechanism design. The event messages drive the above control units with the programmable heuristic knowledge, including the static knowledge, procedural knowledge, and strategic, situation-action behavior knowledge. In this OOCDPSS, a completely transparent environment and a programmable distributed blackboard control mechanism are provided. This environment automatically assists and supervises the progress of cooperative problem solving activities at run time, thereby raising the effective level of use among the preexisting problem solvers. In addition, by using the programmable heuristic knowledge, our approach can be efficiently implemented on the cooperative problem solving plans with a range of configurations. ©1997 John Wiley & Sons, Ltd.     

A blackboard approach to modeling expertise in corporate settlement decisions*

Abstract: The SKADE system models expertise in corporate settlement decisions using the blackboard approach. The full model has four knowledge sources: General Counsel, Attorney, Manager and Insurance Adjuster. The combined expertise from each of these is required to make the settlement decision. A control component in the model coordinates the activities of the various knowledge sources. Based on the latest data entries on the blackboard, the control selects and executes the next knowledge source. The blackboard model reproduces the experts' opportunistic reasoning processes by the interaction between the various knowledge sources. The results of analyses of a hypothetical case through a series of experiments with the SKADE system indicate that the blackboard is an appropriate model for development of multiple cooperative expert systems in the settlement decision domain. Compared to straight rule-based models, this blackboard provides more efficient problem solving. The initial success with the blackboard model suggests that further work needs to be done to see whether more complex models can be built to incorporate a broader range of determinants of settlement decisions.     

基于黑板模型的CGF智能决策系统

为了更加有效地实现CGF实体的智能决策，研究了一种智能决策系统的结构和设计，此设计以黑板系统为模型，通过内置的黑板结构、知识源结构及推理控制策略为CGF提供一个简易、友好的智能决策系统。在决策推理决策中，由于不精确推理算法的使用，使得此智能决策系统决策快速而准确，满足了CGF智能决策的需求。     

Reactive process control using a blackboard architecture

A software architecture to engineer complex process control applications must combine into the same paradigm efficient reactive and real-time functionalities and mechanisms to capture dynamic time-pressured intelligent behaviors, and must provide convenient high level tools to free the programmer from having to think at an unappropriate level of detail. We implement such characteristics into a blackboard framework that builds the basic abstract elements of reactive behavior and the blackboard computational model on top of low level real-time operating system functions. Under this approach, the engineer gets a powerful and flexible high level medium to map a complex system design that requires artificial intelligence techniques, like intelligent monitoring, and reactive planning and execution, with fully support for real-time programming. The paper also reviews other alternatives which have been explored in the past recent years for implementing complex reactive planning and execution systems.     

A BLACKBOARD DATABASE MODEL OF THE DESIGN PLANNING PROCESS IN CONCURRENT ENGINEERING

The basis for an intelligent decision support system for design process planning within a concurrent engineering (CE) environment is the efficient utilization and coordination of planning knowledge that resides within computerized workgroups of multidisciplinary experts. A systems approach may be taken to derive, represent, and utilize the many models of reasoning that might support a human-centric view of planning in a distributed environment. The blackboard database (BB) provides a suitable framework for utilizing these models in a structured manner by representing the planning problem as a loosely coupled hierarchy of partial problems along with the knowledge needed to progressively solve different parts of this problem. This article discusses the development of such a BB system, which is intended to provide the ability to experiment with various control and domain strategies in order to yield insight into more developed and intelligent methods to assist humans in planning the CE design process.     

智能协作控制系统

提出了智能协作控制系统的框架、原理，并介绍了设计方法。建立了基于产生式规则的黑板结构多智能体控制系统，采用多智能体联合问题求解策略，对不同的外部环境(被控对象)，具体设计方法有：任务分配，子问题求解，结果综合，控制级设计。对子问题求解中产生的冲突或无解，如何进行结果综合，以达到最优或次优，是采用重新分配任务，还是更改知识库，或推理方法等有待进一步探讨。