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 59
Page 12
... solution takes the requirements for the life cycle stated above specifically into account, and aims at maximizing the separation and independence between phases and their internal strength and level of aggregation. Before describing ...
... solution takes the requirements for the life cycle stated above specifically into account, and aims at maximizing the separation and independence between phases and their internal strength and level of aggregation. Before describing ...
Page 27
... solution by present expert system technology, or whether there might be a better way (or, possibly, no way) to attack the problem. If expert system technology is not the best solution to the given problem, then the project team should ...
... solution by present expert system technology, or whether there might be a better way (or, possibly, no way) to attack the problem. If expert system technology is not the best solution to the given problem, then the project team should ...
Page 39
... be foreseen and taken into account. • No alternative solution to the problem is being pursued or is expected to be pursued. and • Any requirement for system performance will not involve extensive Choosing an expert system domain 39.
... be foreseen and taken into account. • No alternative solution to the problem is being pursued or is expected to be pursued. and • Any requirement for system performance will not involve extensive Choosing an expert system domain 39.
Page 48
... knowledge. Is a diagnostic solution always achieved in the same way, or are there alternative technique for the different failures that occur? 3. The need for and availability of data at run 48 G.S. Kahn and M. Bauer 2. WHY PROTOTYPE.
... knowledge. Is a diagnostic solution always achieved in the same way, or are there alternative technique for the different failures that occur? 3. The need for and availability of data at run 48 G.S. Kahn and M. Bauer 2. WHY PROTOTYPE.
Page 50
... solutions. Prototypes developed as functional specifications typically focus on capturing the requirements of a system, not the design. In order to achieve desired functionality, a design exploration is required. Prototypes prove useful ...
... solutions. Prototypes developed as functional specifications typically focus on capturing the requirements of a system, not the design. In order to achieve desired functionality, a design exploration is required. Prototypes prove useful ...
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