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.     

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.     

REDSIEX: A Cooperative Network of Expert Systems with Blackboard Architectures

The blackboard architecture, originally developed for the system that permits the comprehension of language, HEARSAY II, has later been used in a great variety of domains and in various environments for the construction of systems. From the classic architecture of HEARSAY II, many applications, generalizations, extensions and refinements have been developed. In this paper we present REDSIEX, (RED de SIstemas EXpertos) which is a network of expert systems within a blackboard architecture, for the cooperation solution of distributed problems. The REDSIEX system inherits various of the elements defined by the architecture of HEARSAY II and incorporates new components and organization. These produce a very characteristic and exclusive global work style in the solution of problems, within a conceptual framework of emergent control. The main structural and functional characteristics of REDSIEX are discussed.     

Knowledge decomposition for a product design blackboard expert system

Product design is a complex process, requiring many design factors and knowledge areas to be considered simultaneously. An expert system with a blackboard architecture is appropriate for representing this variety of factors and areas. However, oftentimes it is unclear how to transform the knowledge into the component knowledge bases of a blackboard expert system. The paper describes a non-directed graph decomposition procedure for transforming the knowledge into knowledge bases as part of an approach for developing a product design blackboard expert system. A wood head golf club design example is provided.     

一个基于面向对象方法的并行黑板系统的设计

本文论述了用面向对象的系统分析与设计方法和面向对象的编程技术构造大型、复杂的并行黑板实时控制系统的思想和方法。文章以四辊冷连轧机为对象给出了一个设计实例并给出了一个通用的实时控制并行黑板结构ＲＴＣＢ。贯穿全文的一个很重要的思想就是要致力于开发面向对象方法和黑板模型的潜在的并行、并发特性以及所构造系统的可扩充性和易维护性。     

Automating maintenance for a one‐way transmitting blackboard system used for autonomous multi‐tier control

The blackboard architecture has particular utility in applications where conclusions must be drawn in the absence of human involvement. Through properly crafted rules, this approach can determine what a collection of data may mean. This can be utilized by other onboard software to limit transmission to only relevant data or conclusions. Some applications, such as robotic exploration, may preclude or severely limit the availability of controller‐to‐craft‐agent communications. In this case, the maintenance of the system must be performed autonomously.This paper discusses common maintenance tasks that may be relevant to a long‐running blackboard‐based system (e.g. clearing extraneous data from the blackboard regularly to improve performance, archiving relevant but infrequently used data for performance enhancement). A system for automating these tasks is presented that is suitable for most blackboard‐style systems. Its particular utility to those that cannot be easily accessed is discussed. Quantitative analysis of the value of removing rules from the system is performed and presented, and these results are extrapolated to several prospective blackboard maintenance approaches.     

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。     

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.     

一种基于黑板模型的多Agent系统通信方法

本文以人工智能领域中的黑板模型为基础 ,提出了在 Internet环境中多 Agent系统 (MAS)的通信方法 .该方法可用于异构的 MAS系统间的通信 .首先把 MAS系统的通信环境划分为不同的层次 ,然后用黑板模型对这些层次进行了描述 .基于这种描述给出了 MAS系统通信用协议和相关参数 .而且 ,还在这些参数中设置了有关服务质量的元素 .     

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     

基于知识的,集成工具化的汽车锻件模具设计过程的仿真思想

提出了一个基于知识的，集成ＣＡＤ／ＣＡＭ模块，有限元分析模块，Ｍｏｔｉｆ界面制作模块的汽车锻件模具设计的仿真系统，此系统可推广到其它类似的模具设计过程仿真。     

一种基于知识模型的CT图像分割方法*

图像自动分割一直是医学图像处理的研究重点。系统由解剖知识模型、图像处理程序和推理机组成。模块之间的通信由黑板控制。该方法提高了医学图像分割的自动化程度和可靠性。由于具有扩展性,该方法为基于知识医学图像的处理提供一个通用的模式。     

A domain-specific software architecture for adaptive intelligentsystems

A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We present a domain-specific software architecture (DSSA) that we have developed for a large application domain of adaptive intelligent systems (AISs). The DSSA provides: (a) an AIS reference architecture designed to meet the functional requirements shared by applications in this domain, (b) principles for decomposing expertise into highly reusable components, and (c) an application configuration method for selecting relevant components from a library and automatically configuring instances of those components in an instance of the architecture. The AIS reference architecture incorporates features of layered, pipe and filter, and blackboard style architectures. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture     

多机器人远程监控系统的多智能体控制结构

针对多机器人远程监控系统信息错综复杂、协作不稳定的问题,建立基于多智能体(Multi-Agent)技术的系统体系结构,描述系统各组件之间的信息交互关系,优化人-机智能分配。分析系统物理结构的特点,提出一种基于Multi-Agent技术的共享控制系统分层体系结构,结合黑板结构和点对点结构,给出Multi-Agent的混合通信模型。针对遥操作系统的特点,设计一种混合型Agent体系结构,举例研究Agent的实现方法。通过多操作者控制机器人保持队形的实验,验证了该混合型Agent体系结构的实用性和有效性。     

An architecture for a self-improving instructional planner for intelligent tutoring systems

Machine instructional planners use changing and uncertain data to incrementally configure plans and control the execution and dynamic refinement of these plans. Current instructional planners cannot adequately plan, replan, and monitor the delivery of instruction. This is due in part to the fact that current instructional planners are incapable of planning in a global context, developing competing plans in parallel, monitoring their planning behavior, and dynamically adapting their control behavior. In response to these and other deficiencies of instructional planners a generic system architecture based on the blackboard model was implemented. This self-improving instructional planner (SUP) dynamically creates instructional plans, requests execution of these plans, replans, and improves its planning behavior based on a student's responses to tutoring. Global planning was facilitated by explicitly representing decisions about past, current, and future plans on a global data structure called the plan blackboard. Planning in multiple worlds is facilitated by labeling plan decisions by the context in which they were generated. Plan monitoring was implemented as a set of monitoring knowledge sources. The flexible control capability for instructional planner was adapted from the blackboard architecture BB1. The explicit control structure of SUP enabled complex and flexible planning behavior while maintaining a simple planning architecture.     

Neural-network-based blackboard demon subsystems

We propose two neural network architectures involving feedforward and probabilistic neural network models to simulate the blackboard demon subsystem, which is responsible for triggering knowledge sources in accordance with the complex monitoring conditions on the hypotheses in the blackboard. Both architectures involve a preprocessor module to perform the transformation between symbolic hypotheses and numerical ones. They learn and record the triggering relationships between hypotheses and knowledge sources in the network links and perform better blackboard monitoring function than the traditional symbolic demon subsystems. In comparison, the probabilistic neural network-like architecture performs better when there is a possibility of using a centralized knowledge representation and when it only involves one-to-one or one-to-many mapping between hypotheses and triggering patterns. The feedforward architecture may be useful when a distributed knowledge representation is possible and when time requirements for training the architecture to learn the complex mappings are not too strict.     

Embedable problem-solving architectures: a study of integratingOPS5 with UMass GBB

The requirements of a problem-solving architecture that can be tightly embedded within other architectures and coexist with multiple instances of itself and of other problem-solvers are discussed. The additional effort needed to produce an embedable problem-solving architecture is minor compared to the substantial increase in applicability of the architecture. A specific need for embedable problem-solvers arose with the University of Massachusetts Generic Blackboard Framework (UMass GBB). UMass GBB is based on the blackboard paradigm, which naturally integrates heterogeneous problem-solving representations as individual knowledge sources (KSs). This need is met by developing general specifications for embedable problem-solving architectures, and the specifications are used to modify the public-domain version of OPS5 in order to embed it as an integral KS language within UMass GBB. The OPS5 modifications result in an easily integrated GBB KS language (distributed with the UMass GBB system) that has been used in several GBB applications     

Galoan: a multi-agent approach to herd cows

This paper describes the team Galoan (it is a local Persian name that means shepherd), one of the participants in the Multi-Agent Programming Contest 2010. We present the agents’ architecture as well as the team strategies and the coordination and cooperation approaches. Our system was developed using the blackboard style and was implemented in Java. In our approach each agent stores its perception in a shared world model which is called blackboard. Coordination has been implemented through a supervisor. The supervisor uses the stored information in the blackboard and coordinates the agents to achieve a goal. Finally, we outline our observations and discuss the performance of our team.     

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.