Blackboard System Research Articles

Simulation of a Blackboard System with Multiple Reasoning for System Identification in Adaptive Control Applications

Adaptive control systems have been developed and used for a number of decades. There are still a number of problems with their operation, which limits their wider industrial adoption. This paper addresses one aspect of adaptive control, namely the on-line system identification of the time-varying dynamic process being controlled. The approach adopted is to use a blackboard system with algorithmic, fuzzy logic, and evolutionary reasoning to identify the underlying time-varying system model. A framework to implement this approach is proposed. The framework is simulated, and the paper describes the choice of language (Smalltalk-80) for, and the development of, this simulator. A number of simulation runs are described and discussed. Based on the simulations it is concluded that the frame work is very effective, particularly with respect to its robustness under the sort of poor conditions experienced in real adaptive control applications. The application of this approach to on-line system identification of a real plant is the principal recommendation.

A Rule-based Extension to the C++ Language

In rule-based systems, sets of rules are applied to known information to generate new, consequential information. The majority of the large number of existing systems1 has been produced with the objective of ease of use, enforcing an English-like syntax in the rules and hiding the control methods from the developer. The method adopted in the current work aims to provide rule-based facilities while maintaining the flexibility and implementation efficiency of a conventional language. This is achieved by extending the features of C++ to permit the development of rule-based systems whose control is decided by the developer. The design can be tailored to the application unrestricted by the normal constraints of the rule-based system, and a framework is made available for the development of multiple expert systems for use in blackboard system applications. This paper describes the approach adopted in the current work, the operation of the system and describes two example implementations. © 1997 John Wiley & Sons, Ltd.

The Negative Information Problem in Mechanical Diagnostics

Condition-based maintenance (CBM) is an emerging technology, which seeks to develop sensors and processing systems aimed at monitoring the operation of complex machinery such as turbine engines, rotor craft drivetrains, and industrial equipment. The goal of CBM systems is to determine the state of the equipment (i.e., the mechanical health and status), and to predict the remaining useful life for the system being monitored. The success of such systems depends upon a number of factors, including: (1) the ability to design or use robust sensors for measuring relevant phenomena such as vibration, acoustic spectra, infrared emissions, oil debris, etc.; (2) real-time processing of the sensor data to extract useful information (such as features or data characteristics) in a noisy environment and to detect parametric changes that might be indicative of impending failure conditions; (3) fusion of multi-sensor data to obtain improved information beyond that available to a single sensor; (4) micro and macro level models, which predict the temporal evolution of failure phenomena; and finally, (5) the capability to perform automated approximate reasoning to interpret the results of the sensor measurements, processed data, and model predictions in the context of an operational environment. The latter capability is the focus of this paper. Although numerous techniques have emerged from the discipline of artificial intelligence for automated reasoning (e.g., rule-based expert systems, blackboard systems, case-based reasoning, neural networks, etc.), none of these techniques are able to satisfy all of the requirements for reasoning about condition-based maintenance. This paper provides an assessment of automated reasoning techniques for CBM and identifies a particular problem for CBM, namely, the ability to reason with negative information (viz., data which by their absence are indicative of mechanical status and health). A general architecture is introduced for CBM automated reasoning, which hierarchically combines implicit and explicit reasoning techniques. Initial experiments with fuzzy logic are also described.

SACM: Semantic agenda control model

Current KBS, that handle large amounts of information from different sources and have different representation formalisms, are structured as less complex modules that process a single source of knowledge and have a single representation formalism, instead of as a single knowledge base that would be unprocessable. The organization and cooperation between the different modules, that is, the system control structure, is crucial for achieving the goal in KBS operation, where the agenda and blackboard models are the control architectures best suited for managing this control. In this paper, we present a new agenda architecture that deals with independent tasks and also takes into account the result of the execution of earlier tasks to decide on whether or not a new task would be added to the agenda, functions that are not contemplated by the current agenda system. This new agenda structure has made it possible to define an object-oriented KBS control model with independent components to specify the agenda itself, the tasks and the justifications, thus providing a robust, flexible, reusable, extendible and generic control structure, making for easy and efficient implementation of applications with complex control. As an example of this, a vocational guidance expert system (HAMLET), is presented which was implemented with this model. 1997 Elsevier Science Ltd

A mechanism for Multimodal Presentation Planning Based on Agent Cooperation and Negotiation

A multimodal presentation planning mechanism must take into consideration the structure of the discourse and the constraints imposed by discourse relations. This requires that different processes that perform multimodal presentation planning be able to communicate with each other. In this article, we introduce a multiagent architecture based on the blackboard system that satisfies this requirement. In addition, we describe a constraint propagation mechanism that transfers plan constraints from one level of the presentation planning process to the next, and we discuss the cooperation and negotiation processes between modality-specific agents in a prototype system that implements the multiagent planning mechanism.

Efficiency Mechanisms for a Class of Blackboard Systems

This paper presents efficient mechanisms for activation, execution and rating that are suitable for use in BB1-style blackboard architectures. We describe a knowledge source compiler that produces match networks and demons for efficient activation and rating while compiling the entire system for increased execution speed. Experiments using the enhancements in a general-purpose blackboard shell illustrate approximately a doubling of run time speed, including an increase in activation speed by a factor of 7.6 on the average. We have also resolved a subclass of blackboard systems that can be compiled down to the machine level by using a condensed representation where low-level blackboard accesses are replaced by vector references. Our analysis shows that the time complexity of the execution cycle of a condensed system is faster than the conventional approach by the ratio of the time required for blackboard retrievals to the time required for vector element retrievals. In practice, this ratio is approximately four orders of magnitude.

Distributed Object–Oriented Blackboard Model for Integrated Design of Steel Structures

Distributed computing on a cluster of workstations connected via a local area network provides a cost–effective approach to high–performance computing. The goal of this research is to lay the foundation for developing maintainable, extendable, and reusable programmer–defined object–oriented software systems on a cluster of networked workstations. A distributed object–oriented blackboard model (OOBM) is presented for integrated design of large structures on a cluster of workstations. The model includes an object–oriented alternative to model the functions of message passing and process control required in a distributed processing environment. The operational idea behind the distributed OOBM is to perform two missions iteratively until the desired solution is found. The first mission is to pass and monitor data messages through network communication using a network file server. The second mission is to generate a number of processes at heterogeneous workstations using appropriate process–generating models and techniques. The models and concepts developed in this research are applied to the problem of integrated design of steel structures.

Design and evaluation of a hierarchical distributed system for programming exercise assistance

This paper aims at quality improvement of a programming exercise course, and proposes a framework for the exercise assist system with the following features:(1) an exercise system, with a description of the structural algorithm as its core; (2) the assist service, utilizing the teacher and operational knowledge; (3) the assist environment adapted to the percentages of students with varous degrees of progress. Then, defining the pair consisting of the student number and the task number as the unit in the exercise assist operation, it is shown that the relation between the state of the student and the assist service can be interpreted by the blackboard model. A reasonable realization of the forementioned model is discussed, considering both the service response and the effective use of the resources such as the processor and the memory. A construction scheme is proposed, based on the hierarchical blackboard. A prototype system is constructed based on the proposed concept. By a benchmark test, the relation between the response time of the assist service and the implementation memory capacity of the workstation is shown, and the superiority of the hierarchical structure over the nonhierarchical structure is quantitatively demonstrated. As an item of the performance evaluation, an experiment is used to analyze the relation between the system response time and the psychological satisfaction of the user. The threshold for descriminating satisfaction and dissatisfaction of the user is determined. © 1997 Scripta Technica, Inc. Syst Comp Jpn, 28 (1): 34–45, 1997

On cooperating—distributed extended limited 0L systems

Cooperating—distributed grammar systems [1] constitute a formal model of the blackboard model for problem solving. In [10], we have replaced the grammars in such systems by K-limited OL systems [9] each having the same alphabet. In this paper we generalize these cooperating—distributed limited OL systems by allowing arbitrary alphabets of the underlying systems and by adding a terminal alphabet. By these means, the generative power of the systems is increased. For these extended cooperating—distributed limited OL systems we can define quite a lot of different language families. But despite of the additional generative mechanisms, each such language family is included in the family of 1-limited ET0L languages.

Cooperative Design, Manufacturing and Assembly of Complex Products

As customer requirements rise and time to market shrinks the need for global scurcing of development, manufacturing, and assembly capacity increases. This paper presents a method for integrating design and manufacturing engineers from different companies into a virtual value-adding team. The method is based on network theory using circuits to describe the flow of information originating from customer requirements. These circuits sustain the context of specific activities to the overall task during requirements analysis, design, and system integration. A blackboard model based on the combination of these circuits together with design structure matrices visualizes and guides the course of action during a product development project. This blackboard enables international development consortia to work jointly on new products and processes in a selforganized manner with limited effort for project management. The design of a public transport system serves as an example to illustrate this method.

A knowledge-based task-level programming and execution environment for robots

A knowledge-based framework to support task-level programming and operational control of robots is described. Our bask intention is to enhance the intelligence of a robot control system so that it may carefully coordinate the interactions among discrete, asynchronous and concurrent events under the constraints of action precedence and resource allocation. We do this by integrating both off-line and on-line planning capabilities in a single framework. The off-line phase is equipped with proper languages for describing workbenches, specifying tasks, and soliciting knowledge from the user to support the execution of robot tasks. A static planner is included in the phase to conduct static planning, which develops local plans for various specific tasks. The on-line phase is designed as a dynamic control loop for the robot system. It employs a dynamic planner to tackle any contingent situations during the robot operations. It is responsible for developing proper working paths and motion plans to achieve the task goals within designated temporal and resource constraints. It is implemented in a distributed and cooperative blackboard system, which facilitates the integration of various types of knowledge. Finally, any failures from the on-line phase are fed back to the off-line phase. This forms the interaction between the off-line and on-line phases and introduces an extra closed loop opportunistically to tune the dynamic planner to adapt to the variation of the working environment in a long-term manner.

Adding Hard Real-Time Tasks to Artificial Intelligence Environments

In this paper, we present a task model suitable for providing predictability to artificial intelligence tasks, that allows us to incorporate AI techniques in real-time systems guaranteeing their response time. Furthermore, we propose a Real-Time Artificial Intelligence System architecture based on the previous task model and on the blackboard model, which uses the feasibility theory for fixed priority scheduling in order to guarantee the minimum system quality required.

Object-oriented blackboard models for integrated design of steel structures

An object-oriented model-based approach is presented for the integrated design of large structures consisting of hundreds or thousands of members. We model the problem of integrated design of large structures by a hierarchy of cooperating knowledge bases. A dynamic knowledge identification and isolation (DKII) strategy is developed for effective management of knowledge bases (KBs). For efficient storage of KBs, a hierarchical arrangement in the form of a knowledge storage pyramid (KSP) is created. An inheritance gene object-oriented programming (IGOOP) model is presented for constructing the hierarchical relationship among KBs through a rule-based KB allocation technique. An object-oriented blackboard model (OOBM) is developed where the blackboard verifies the attributes of each specialist (KB) dynamically operates on each KB, and monitors continuously the contributions generated by each KB. The major components of OOBM are described. The models and concepts developed in this research are applied to the design of steel structures.

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.

Implementation of multistep fuzzy reasoning shell

AbstractRecently, there have been many trials conducted to develop fuzzy inference systems that can handle the subjective decision of the expert. A problem in the fuzzy control system is that it is an inference composed of only a single step, and cannot be applied to the decision‐making assist or diagnosis, where the inference is made in multisteps. Another point is that the rules of the inference cannot be described for each knowledge source, which has been the conventional inference shell (deterministic inference shell).This paper proposes a fuzzy inference shell which can realize the multistep inference using the blackboard model. The proposed shell uses its own rule description language to represent the knowledge, and the description can be made by combining the new method with the conventional deterministic inference.Using the divided knowledge blocks, the multi‐step fuzzy inference can be realized using the blackboard model. The search function also is provided that can track the inference path in the multistep inference. This paper describes the basic configuration of such a shell.

Logistics information system auditing using expert system technology

This paper brings together two methodological strands of thinking. These are the managerial problem solving methodology of Logistics Information System auditing and the structured development of expert system technology. The investment being made in logistics in organizations is enormous and, although much effort has been devoted to creating structured methods to aid the development of information systems to support these organizations' logistics, the area of Logistics Information System auditing remains less developed. The major aim of this paper is to provide a systemic approach of the application of expert system technology to Logistics Information System auditing. Taking a strategic view of Management Information System (MIS) in logistics, this paper describes the application of INFAUDITOR, an audit expert system, to logistics information systems auditing. INFAUDITOR has two fundamental features. First, it covers all domains of information systems, managerial (like logistics) as well as technical aspects. Secondly, it helps to determine, in a given audit situation, the respective importance that should be given to the different audit domains and tests of control. INFAUDITOR can be viewed as consisting of several expert systems as in blackboard systems. Its fact bases include the characteristics of the enterprise, its logistics information system and the audit objectives. Its rule bases encompass the audit criteria represented as a hierarchical tree. INFAUDITOR is used to assess the ability of a Logistics Information System (LIS) to provide decision makers with relevant, timely information for designing, planning and maintaining an efficient production system, for securing materials necessary for production, and for facilitating achievement of low operating and maintenance costs. We present and discuss results obtained by using INFAUDITOR in auditing the logistics Management Information System of a large European company.

How to implement a naturalistic model of abstracting: Four core working steps of an expert abstractor

Four working steps taken from a comprehensive empirical model of expert abstracting are studied in order to prepare an explorative implementation of a simulation model. It aims at explaining the knowledge processing activities during professional summarizing. Following the case-based and holistic strategy of qualitative empirical research, we develop the main features of the simulation system by investigating in detail a small but central test case—four working steps where an expert abstractor discovers what the paper is about and drafts the topic sentence of the abstract. Following the KADS methodology of knowledge engineering, our discussion begins with the empirical model (a conceptual model in KADS terms) and aims at a computational model which is implementable without determining the concrete implementation tools (the design model according to KADS). The envisaged solution uses a blackboard system architecture with cooperating object-oriented agents representing cognitive strategies and a dynamic text representation which borrows its conceptual relations in particular from RST (Rhetorical Structure Theory). As a result of the discussion we feel that a small simulation model of professional summarizing is feasible.

Hybrid blackboard model for feature interactions in process planning

This paper describes a hybrid blackboard model designed for process planning of prismatic parts on CNC machine tools in a batch manufacturing environment. This hybrid blackboard model uses mixed-type reasoning to handle feature interactions by combining the forward chaining for feature sequencing and the backward chaining for the construction of a process plan. In such a hybrid model, the human problem-solving strategies are decoupled from the tools for analysis and sorting algorithms. The central algorithm has four steps: (1) define the important information for features and feature-related concerns; (2) prioritize the given feature according to the given constraints and sorting guideline; (3) sequence the features; and (4) attach the needed operations to the features in machine/process/feature/set-up/tool/time/cost format.

Compositional refinements in multiple blackboard systems

Compositional refinements in multiple blackboard systems

Intelligent finite element mesh generation

A knowledge-based and automatic finite element mesh generator (INTELMESH) for two-dimensional linear elasticity problems is presented. Unlike other approaches, the proposed technique incorporates the information about the object geometry as well as the boundary and loading conditions to generate an a priori finite element mesh which is more refined around the critical regions of the problem domain. INTELMESH uses a blackboard architecture expert system and the new concept of substracting to locate the critical regions in the domain and to assign priority and mesh size to them. This involves the decomposition of the original structure into substructures (or primitives) for which an initial and approximate analysis can be performed by using analytical solutions and heuristics. It then uses the concept of wave propagation to generate graded nodes in the whole domain with proper density distribution. INTELMESH is fully automatic and allows the user to define the problem domain with minimum amount of input such as object geometry and boundary and loading conditions. Once nodes have been generated for the entire domain, they are automatically connected to form well-shaped triangular elements ensuring the Delaunay property. Several examples are presented and discussed. When incorporated into and compared with the traditional approach to the adaptive finite element analysis, it is expected that the proposed approach, which starts the process with near optimal initial meshes, will be more accurate and efficient.