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 85
Page 6
... knowledge acquisition, validation, and refinement. The work done at the National Archives and Records Administration ... representation, and prototype implementation. Specific automatic tools, well integrated with the methodology, are capable ...
... knowledge acquisition, validation, and refinement. The work done at the National Archives and Records Administration ... representation, and prototype implementation. Specific automatic tools, well integrated with the methodology, are capable ...
Page 13
... knowledge representation methods and reasoning mechanisms is proposed, which serves as a basis for developing a draft project plan. Plausibility, which is the main concern of Phase 1, comprises the following five main aspects ...
... knowledge representation methods and reasoning mechanisms is proposed, which serves as a basis for developing a draft project plan. Plausibility, which is the main concern of Phase 1, comprises the following five main aspects ...
Page 16
... knowledge acquisition activity is performed in order to identify an appropriate conceptual model for the entire problem considered. The technical choices concerning architecture, knowledge representation methods and reasoning mechanisms ...
... knowledge acquisition activity is performed in order to identify an appropriate conceptual model for the entire problem considered. The technical choices concerning architecture, knowledge representation methods and reasoning mechanisms ...
Page 48
... Knowledge-based systems are typically composed of three architectural units: the problem solver, the knowledge base ... representation of order should there be? 2. The degree of procedural regularity in the use of knowledge. Is a ...
... Knowledge-based systems are typically composed of three architectural units: the problem solver, the knowledge base ... representation of order should there be? 2. The degree of procedural regularity in the use of knowledge. Is a ...
Page 49
... knowledge vs. what must be acquired at run time? What are reasonable default assumptions? Is it reasonable, for ... representation and problem solver enables a preliminary capture of knowledge whose use can be explored from alternative ...
... knowledge vs. what must be acquired at run time? What are reasonable default assumptions? Is it reasonable, for ... representation and problem solver enables a preliminary capture of knowledge whose use can be explored from alternative ...
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