: Artificial intelligence software has for many years made extensive use of graphics facilities. However, knowledge engineers have not had access to visual programming tools which assist them during the critical early phases of knowledge acquisition. Moreover, during later phases of knowledge base debugging, knowledge engineers have had to work with program tracing tools (whether graphical or textual) which are inherently incapable of scaling up to the monitoring demands imposed by large, heterogeneous knowledge bases. To address these deficiencies, and to satisfy the needs of knowledge engineers throughout the software design, development, and debugging cycle, we have developed several novel visual programming and program visualization techniques aimed at knowledge engineers. Foremost among these are (i) a hypertext transcript analyser from which conceptual models can be generated; (ii) a `direct graph manipulation' sketchpad which allows the knowledge engineer to sketch out objects a...

CODE4 is a general-purpose knowledge management system, intended to assist with the common knowledge processing needs of anyone who desires to analyse, store, or retrieve conceptual knowledge in applications as varied as the specification, design and user documentation of computer systems; the construction of term banks, or the development of ontologies for natural language understanding. This paper provides an overview of CODE4 as follows: We first describe the general philosophy and rationale of CODE4 and relate it to other systems. Next, we discuss the knowledge representation, specifically designed to meet the needs of flexible, interactive knowledge management. The highly-developed user interface, which we believe to be critical for this type of system, is explained in some detail. We finally describe how CODE4 is being used in a number of applications. 1. Introduction 1.1 Rationale for CODE4 This paper describes the main aspects of an interactive, multi-functional, knowledge ma...

This paper reports on the development of a realistic knowledge-based application using the MOBAL system. Some problems and requirements resulting from industrial-caliber tasks are formulated. A step-by-step account of the construction of a knowledge base for such a task demonstrates how the interleaved use of several learning algorithms in concert with an inference engine and a graphical interface can fulfill those requirements. Design, analysis, revision, refinement and extension of a working model are combined in one incremental process. This illustrates the balanced cooperative modeling approach. The case study is taken from the telecommunications domain and more precisely deals with security management in telecommunications networks. MOBAL would be used as part of a security management tool for acquiring, validating and refining a security policy. The modeling approach is compared with other approaches, such as KADS and stand-alone machine learning. What online ML can do for KA -...

First-order predicate logic essentially is a language to express knowledge concerning objects and relationships between objects in a domain. Many medical problems can be cast naturally in such terms. In this paper the suitability of logic as a knowledge-representation formalism in building medical expert system is investigated. In particular, we investigate the logical representation of three typical reasoning models in medicine: diagnostic, anatomical and causal reasoning. It turns out that each of these models has its own characteristic logical structure. Furthermore, the pragmatics of using theorem-proving techniques in consulting such logic-based medical expert systems is discussed. In particular, attention is paid to the use of a meta-level architecture to improve the applicability of theorem-proving techniques in building expert systems.

iv List of Tables vii List of Figures viii Chapter 1 Introduction 1 1.1 Motivation : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.2 Background : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.3 KM : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 1.3.1 Introduction : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 1.3.2 Slots are Represented as Frames, Too : : : : : : : : : : : : : : : : : : : : : : 3 1.3.3 Definitions : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 1.3.4 Annotations : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 1.3.5 Addresses : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 6 1.3.6 Editing Commands : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 6 1.3.7 Inverses : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : ...

Process engineering involves a search for new models of organising work. This synthesis task can become quite difficult and time-consuming as the amount of detail required and interactions between activities increases. Domain independent AI planning offers some promising techniques and representations to assist in this effort. One of the major impediments to transferring this technology to applied, real-world settings is the difficulty encountered in building the domain model which is used in the automated generation of these plans. Competence, as well as good tools, is necessary to carry out this task. A plan domain methodology should be available which provides structured organisational development activities. Users need to know what tasks they have to perform: for each step, information must be available about what input will be needed, and what output will be required, what is to be done and how it can be done well. This paper presents the Common Process Methodology (CPM) which aim...