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 61
Page 4
... requirements for an expert system life cycle. In section 4 a life cycle for expert systems is proposed and its main features are discussed. Section 5 focuses on the issue of developing from the proposed life cycle a complete methodology ...
... requirements for an expert system life cycle. In section 4 a life cycle for expert systems is proposed and its main features are discussed. Section 5 focuses on the issue of developing from the proposed life cycle a complete methodology ...
Page 6
... requirement analysis is performed utilizing data flow diagrams and system development is supported by standard structured programming techniques. Quite differently from the large majority of the authors, De Salvo, Glamm, and Liebowitz ...
... requirement analysis is performed utilizing data flow diagrams and system development is supported by standard structured programming techniques. Quite differently from the large majority of the authors, De Salvo, Glamm, and Liebowitz ...
Page 8
... requirements This section is devoted to discuss two main points: why a life cycle for expert systems and, what should the concept of life cycle for an expert system be. To both these questions we will propose an answer that will serve ...
... requirements This section is devoted to discuss two main points: why a life cycle for expert systems and, what should the concept of life cycle for an expert system be. To both these questions we will propose an answer that will serve ...
Page 9
... requirements. The first set is made up of general engineering requirements common to several technology fields (information system design and software production have been specifically taken into account) and deriving from the need of ...
... requirements. The first set is made up of general engineering requirements common to several technology fields (information system design and software production have been specifically taken into account) and deriving from the need of ...
Page 10
... requirements is to explore whether the results obtained in the field of software engineering (Boehm, 1981; Myers, 1976; Yourdon and Constantine, 1978) can be transferred, to some extent, to the new area of expert system technology ...
... requirements is to explore whether the results obtained in the field of software engineering (Boehm, 1981; Myers, 1976; Yourdon and Constantine, 1978) can be transferred, to some extent, to the new area of expert system technology ...
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