Topics in Expert System Design: Methodologies and ToolsC. Tasso, G. Guida Elsevier, 2014 M06 28 - 447 pages Expert Systems are so far the most promising achievement of artificial intelligence research. Decision making, planning, design, control, supervision and diagnosis are areas where they are showing great potential. However, the establishment of expert system technology and its actual industrial impact are still limited by the lack of a sound, general and reliable design and construction methodology.This book has a dual purpose: to offer concrete guidelines and tools to the designers of expert systems, and to promote basic and applied research on methodologies and tools. It is a coordinated collection of papers from researchers in the USA and Europe, examining important and emerging topics, methodological advances and practical experience obtained in specific applications. Each paper includes a survey introduction, and a comprehensive bibliography is provided. |
From inside the book
Results 1-5 of 87
Page 18
... Figure 1. The five phases of the life cycle illustrated above are strictly sequential: after the goals of a phase have been completely accomplished and specific results have been produced, the development continues with the following ...
... Figure 1. The five phases of the life cycle illustrated above are strictly sequential: after the goals of a phase have been completely accomplished and specific results have been produced, the development continues with the following ...
Page 19
... system +- - => development and installation and manuals W operation, maintenance, and extension Figure 1 - Expert system life cycle. specifically into account some of the peculiarities of the expert. Building expert systems 19.
... system +- - => development and installation and manuals W operation, maintenance, and extension Figure 1 - Expert system life cycle. specifically into account some of the peculiarities of the expert. Building expert systems 19.
Page 20
... Figure 2 illustrates this concept. -> task and activity definition life cycle + -> technique methods = -- management methods development methodology Figure 2 - From expert system life cycle to development methodology. Going into more ...
... Figure 2 illustrates this concept. -> task and activity definition life cycle + -> technique methods = -- management methods development methodology Figure 2 - From expert system life cycle to development methodology. Going into more ...
Page 57
... (figure 4-1). The model is composed of five key objects, each of which is represented as a CRL schema: the System, Knowledge-Base, Problem-Solver, Interface, and Environment. Each of these objects has important attributes, relations, and ...
... (figure 4-1). The model is composed of five key objects, each of which is represented as a CRL schema: the System, Knowledge-Base, Problem-Solver, Interface, and Environment. Each of these objects has important attributes, relations, and ...
Page 60
... figure 5-1). RPS provides a robust mock-up of the future system -- the default actions don't do a whole lot, but they keep the system integral and crash-proof. Starting with a robust, functioning system, the developer can turn quickly ...
... figure 5-1). RPS provides a robust mock-up of the future system -- the default actions don't do a whole lot, but they keep the system integral and crash-proof. Starting with a robust, functioning system, the developer can turn quickly ...
Contents
25 | |
45 | |
Development tools | 179 |
Knowledge acquisition and modeling | 231 |
Validation and evaluation | 351 |
Further reading | 417 |
A STRUCTURED BIBLIOGRAPHY | 419 |
LIST OF CONTRIBUTORS | 437 |
AUTHOR INDEX | 441 |
Other editions - View all
Topics in Expert System Design: Methodologies and Tools Giovanni Guida,Carlo Tasso Snippet view - 1989 |
Common terms and phrases
abstract activities AI Magazine application approach Artificial Intelligence attribute backward chaining behavior Breuker Building Expert Systems cognitive complete components Computer concepts conceptual model construction context cycle decision defined described diagnosis domain expert domain knowledge environment example Expert System Design expert system development expert system evaluation expert system technology expertise facilities Figure formal function goal graphical heuristics identified implementation important inductive inference input instance integrated interaction interface KADS KCML knowledge acquisition knowledge base Knowledge Craft knowledge elicitation knowledge engineer knowledge representation knowledge-based systems KRITON language layer LISP machine machine learning metaclasses methodology methods model-based reasoning MYCIN objects operations OPS5 output performance phase problem solving Proc programming Prolog protocol analysis prototype refinement relations reliability repertory grid represent requirements rule-based rules selection shells software engineering solution specific strategies structure task techniques Topics in Expert types validity values