Knowledge-based Program Research Articles

Reasoning with worlds and truth maintenance in a knowledge-based programming environment

In traditional knowledge-based system development environments, the fundamental representational building blocks are mechanisms such as frames, rules, and attached procedures. The KEE system has been extended to include both a context (worlds) system and a truth maintenance system.

Knowledge-based successive linear programming for linearly constrained optimization

Combining knowledge engineering technology with some operations research algorithms will get novel efficient optimization methods. As an example, this paper discusses a knowledge-based successive linear programming method for linearly constrained optimization problems. In this new method we use both traditional successive linear programming algorithm in operations research and the knowledge base which is constructed with the expertise of an optimization expert and valuable experience data, so that this knowledge-based program can solve optimization problems somewhat like a human expert who is great at operations research and has a lot of practical experience of problem-solving. The improvement of efficiency in problem-solving depends mainly on the skilful use of plausible reasoning based on incomplete experience knowledge. In addition, man-machine interaction during the computation procedures is also used. Finally, two numerical examples illustrate that the proposed method is much more flexible and efficient than the traditional operations research algorithms concerned.

Direct manipulation of an object store

Integrated project support environments (IPSEs) are intended to provide a cohesive and integrated set of tools to support the process of design and development in software engineering projects. Much current research is concentrated on maximising the degree to which these tools can be integrated. This paper briefly describes the architecture of a prototype IPSE which attempts to achieve a high degree of integration using techniques drawn from the disciplines of intelligent knowledge-based systems, office automation and object-oriented programming. The remainder of the paper deals with the design of a user interface to the IPSE based on direct manipulation. It argues that this provides a consistent and integrated method with which users can interact with the objects in the IPSE's object store.

A case study: acquiring strategic knowledge for expert system development

The authors focus on methodological issues that establish knowledge engineering as an alternative to structured analysis and design, concentrating on the acquisition of strategic knowledge as an implementation structure determinant. They analyze benefits derived from applying expert systems in cellular telecommunications systems, discuss related artificial intelligence work, define structural characteristics of knowledge-based systems, examine a verbal problem-solving protocol from an expert, describe a prototypical knowledge-based program, and review methods and results. They discuss the role of deep knowledge in maintenance tasks, present the resulting system design, and examine the relevant development methodology.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Granularity issues in a knowledge-based programming environment

Marvel is a knowledge-based programming environment that assists software development teams in performing and coordinating their activities. While designing Marvel, several granularity issues were discovered that have a strong impact on the degree of intelligence that can be exhibited, as well as on the friendliness and performance of the environment. The most significant granularity issues include the refinement of software entities in the software database and decomposition of the software tools that process the entities and report their results to the human users. This paper describes the many alternative granularities and explains the choices made for Marvel.

Knowledge-Based Program Debugging Systems

No one likes to debug programs, and there is no way to automate the task. However, knowledge-based approaches offer some possibilities for the future.

Applying AI in jigs and fixtures design

In process planning, the correct selection of fixtures and work holding devices represents an important specification in addition to cutting tool requirements. The arrival at an appropriate fixture design traditionally consists of several phases: careful study of a product specification, retrieval of any existing similar designs, and manual selection of fixture elements based on catalogues and items available in the shop. This procedure depends largely on the knowledge and experience of a tool designer and is both time-consuming and expensive. In addition, manual design procedure does not lend itself readily to computerization. This paper reports the development of fixture design procedure using artificial intelligence. The basic fixture elements are divided into three essential categories: clamping elements, positioning and guiding elements, supporting and base elements. A knowledge-based program structure is used to decide on the appropriate fixture with respect to a particular workpiece specification. The drawing of the elements is then parametrically constructed with an interface program calling standard commands from a drafting package. The elements are assembled interactively to form the final description of the fixture.

Knowledge-based systems: A qualitative formalism

This paper examines knowledge-based systems (KBS's) and considers how they may be applied in the social sciences. KBS's are programs which use artificial intelligence techniques to solve complex problems. Characteristics of KBS's are illustrated with an example knowledge-based program (“N-ACT”) written in PROLOG which uses Goffman's dramaturgical model to analyze social interaction. The paper argues that KBS's offer a qualitative formalism capable of being applied to concepts and phenomena which have been beyond the scope of traditional mathematical models. KBS's can create explicit, reproducible, logically powerful knowledge systems while avoiding the Procrustean bed of mathematical formalism.

Knowledge-based programming: A survey of program design and construction techniques

An application of artificial intelligence (AI) to the development of software is presented for the construction of efficient implementations of programs from formal high-level specifications. Central to this discussion is the notion of program development by means of program transformation. Using this methodology, a formal specification is compiled (either manually or automatically) into an efficient implementation by the repeated application of correctness-preserving, source-to-source transformations. The author considers techniques for data structure selection, the procedural representation of logic assertions, store-versus-compute, finite differencing, loop fusion, and algorithm design methods presented from the point of view of algorithm design and high-level program optimization.

The LDA - an integrated diagnostics tool

In this paper we describe the Logic Designer's Apprentice (LDA). The LDA is a knowledge-based computer program (an "expert system") that designs digital electronic circuits. The LDA extends existing CAD/CAE capabilities by providing a computer aid to the design process, supplementing those that assist the drafting, layout, and simulation processes. It seeks to ensure that appropriate testability (and in the future, other "ility") features are incorporated during the earliest stages of design in accord with the guidelines defined for Integrated Diagnostics. We discuss issues relevant to the engineering development of other knowledge-based tools needed for Integrated Diagnostics including tool selection and choice of knowledge representation.

The development of integrated geo-information systems

Abstract The paper provides a review of research and development in the field of integrated geo-information systems (IGIS) in general and at the Natural Environment Research Council's Thematic Information Service in particular. Advanced data-structures based on quadtrees are emphasized and tesseral addressing techniques and intelligent knowledge-based system approaches introduced. The paper first identifies how digital cartography and remote sensing have developed and merged within the IGIS concept. Recognition of the need for IGIS systems has stimulated research which increasingly is being based on hierarchical data models and incorporating knowledge-based programming techniques. A number of relevant research programmes are reviewed before presenting a more detailed description of NERC research into spatial data-base design, spatial addressing and arithmetic, knowledge-based image segmentation and classification and an expert system for map and graphic output. The paper concludes by identifying those key...

WEAVER: A Knowledge-Based Routing Expert

WEAVER, a channel/switchbox knowledge-based routing program, simultaneously considers all the important routing metrics including 100 percent routability, minimum routing area, minimum wire length, and the minimum number of vias. It allows prerouted nets and user interaction throughout the entire routing process, while relaxing the unnecessary contraints of assigning different directions?constraints imposed by all of the current channel and switchbox routers. A grid-based router using two interconnection layers, WEAVER can be easily expanded to route any shape routing area such as T or +. Implemented in OPSS, a production system language, WEAVER routinely produces routings requiring less area than routers that focus on a single routing metric.

The Operator's Assistant--An Intelligent, Expandable Program for Power System Trouble Analysis

This paper describes two knowledge-based programs. The first simulates the behavior of automatic protection schemes in power networks. The second is an expert system for the diagnosis of faults. Both are coded in OPS5--a widely available language for writing rule-based programs. The user and the programs communicate over a Blackboard which is a database for messages. The Blackboard has been organized so that the addition of new programs, whether knowledge-based or algorithmic, will be relatively easy.

Knowledge-Based Programming

Knowledge-Based Programming

A knowledge-based program for diagnosing metallurgical failures

Failure analysis of structures, a component of the design process, attempts to minimize the costs of mechanical failure by recommending changes in the geometry, materials, processing, or servicing of critical items in order to increase structural reliability. This paper presents a model of failure analysis reasoning and demonstrates techniques of artificial intelligence (AI) that use this model to solve difficult problems of data interpretation. Experiences with a rule-based expert system are used to illustrate problems of knowledge organization and management as the domain of the program gets very large.

Interfacing expert systems with design databases in integrated CAD systems

Knowledge-based and expert systems will be important components of future integrated CAD systems. Flexibility and adaptability are of prime importance in incorporating such components into a CAD system. A model of a distributed network DBMS, using knowledge-based programming techniques, for interfacing KBS-to-DBMS is presented. In this model, the description of the data model of each KBS and DBMS component of the CAD system is represented as knowledge description of the data model of each kBS independent of one another. Each component issues and receives data requests in terms of its own data model, and has no knowledge of the syntax, structure and operation of the other components of the system. KADBASE, a prototype of such a flexible interface, under development is described. It demonstrates an approach to developing an integrated, is distributed CAD systems containing a variety of heterogeneous expert systems and design databases.

An expert diagnostic program for dermatology

The first knowledge-based medical consultation program for dermatology is reported. This program uses SEEK, a new facility within the Rutgers University EXPERT system. Our current model gives a differential diagnosis for 13 different tumors with an overall accuracy of 84%. The model uses a formal criteria-based knowledge representation scheme. In addition, the first visually indexed database in dermatology has been developed.

Future CAD systems

The paper discusses conceptual changes observed as CADCAM systems progress from one generation to another. The influence of representation technology on concepts and methods in CADCAM is discussed, and then the influences of communication between computers, and of knowledge-based programs are considered. Taken together, these various aspects of computer technology throw light on possible scenarios for the future working environment.

Knowledge-based debugging

Robert Balzer began the session by presenting an overview of where debugging fits into knowledge-based programming systems. He distinguished between differences in &lt;italic&gt;paradigm&lt;/italic&gt; (the traditional software engineering approach in which the source code is the first formal representation vs. the operational specification approach in which the specification is both formal and &lt;italic&gt;executable&lt;/italic&gt; and from which the implementation is formally derived) and differences in &lt;italic&gt;technology&lt;/italic&gt; (traditional debuggers vs. knowledge-based tools), pointing out that it is possible to use traditional debugging techniques with the operational specification paradigm as well as use knowledge-based tools with the traditional software engineering paradigm. Balzer presented the operational specification paradigm for software development. The basic idea is that an implementation is derived from a specification through transformations chosen by the programmer and applied by the system. Assuming each transformation is correct, the resulting implementation will accurately reflect the intentions of the specification.

Knowledge-based debugging

Robert Balzer began the session by presenting an overview of where debugging fits into knowledge-based programming systems. He distinguished between differences in &lt;italic&gt;paradigm&lt;/italic&gt; (the traditional software engineering approach in which the source code is the first formal representation vs. the operational specification approach in which the specification is both formal and &lt;italic&gt;executable&lt;/italic&gt; and from which the implementation is formally derived) and differences in &lt;italic&gt;technology&lt;/italic&gt; (traditional debuggers vs. knowledge-based tools), pointing out that it is possible to use traditional debugging techniques with the operational specification paradigm as well as use knowledge-based tools with the traditional software engineering paradigm. Balzer presented the operational specification paradigm for software development. The basic idea is that an implementation is derived from a specification through transformations chosen by the programmer and applied by the system. Assuming each transformation is correct, the resulting implementation will accurately reflect the intentions of the specification.