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. |
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Page 4
... identification, knowledge acquisition, and iterative development of the knowledge base. Moreover, important methodological topics such as project management, documentation, etc. are not mentioned at all. Nevertheless, this work has two ...
... identification, knowledge acquisition, and iterative development of the knowledge base. Moreover, important methodological topics such as project management, documentation, etc. are not mentioned at all. Nevertheless, this work has two ...
Page 5
... identification and system technical and organizational feasibility. Second, some aspects of expert system project management, such as identification and acquisition of the needed resources, organization of the interaction with the ...
... identification and system technical and organizational feasibility. Second, some aspects of expert system project management, such as identification and acquisition of the needed resources, organization of the interaction with the ...
Page 9
... identified the following set of specific requirements: - It should be explorative, i.e. it should allow both system specification and design to proceed incrementally, experimenting alternative problem solving approaches. This implies a ...
... identified the following set of specific requirements: - It should be explorative, i.e. it should allow both system specification and design to proceed incrementally, experimenting alternative problem solving approaches. This implies a ...
Page 10
... identification of a set of currently unsolved needs and exigencies, which motivate the main characteristics of our life cycle definition. These are shortly described below: - In expert system development decisions about project ...
... identification of a set of currently unsolved needs and exigencies, which motivate the main characteristics of our life cycle definition. These are shortly described below: - In expert system development decisions about project ...
Page 11
... identification of what knowledge is needed to achieve a given behavior, favouring in such a way a declarative style of programming. The features listed above show that expert systems are substantially different from traditional software ...
... identification of what knowledge is needed to achieve a given behavior, favouring in such a way a declarative style of programming. The features listed above show that expert systems are substantially different from traditional software ...
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 |
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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