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Knowledge Engineering: Building Cognitive Assistants for Evidence-based Reasoning

Autor Gheorghe Tecuci, Dorin Marcu, Mihai Boicu, David A. Schum
en Limba Engleză Hardback – 7 sep 2016
This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of intelligent agents that use knowledge and reasoning to perform problem solving and decision-making tasks. It covers the main stages in the development of a knowledge-based agent: understanding the application domain, modeling problem solving in that domain, developing the ontology, learning the reasoning rules, and testing the agent. The book focuses on a special class of agents: cognitive assistants for evidence-based reasoning that learn complex problem-solving expertise directly from human experts, support experts, and nonexperts in problem solving and decision making, and teach their problem-solving expertise to students. A powerful learning agent shell, Disciple-EBR, is included with the book, enabling students, practitioners, and researchers to develop cognitive assistants rapidly in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cybersecurity, law, forensics, medicine, and education.
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Specificații

ISBN-13: 9781107122567
ISBN-10: 1107122562
Pagini: 480
Ilustrații: 350 colour illus. 59 tables
Dimensiuni: 183 x 262 x 25 mm
Greutate: 1.16 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States

Cuprins

1. Introduction; 2. Evidence-based reasoning: connecting the dots; 3. Methodologies and tools for agent design and development; 4. Modeling the problem-solving process; 5. Ontologies; 6. Ontology design and development; 7. Reasoning with ontologies and rules; 8. Learning for knowledge-based agents; 9. Rule learning; 10. Rule refinement; 11. Abstraction of reasoning; 12. Disciple agents; 13. Design principles for cognitive assistants.

Recenzii

'At the pole opposite to statistical machine learning lies disciplined knowledge engineering. This book gives a new and comprehensive journey on the approach to AI as symbol manipulation, putting most of the relevant pieces of knowledge engineering together in a refreshingly interesting and novel way.' Edward Feigenbaum, Stanford University, California
'This well-written book is a much-needed update on the process of building expert systems. Gheorghe Tecuci and colleagues have developed the Disciple framework over many years and are using it here as a pedagogical tool for knowledge engineering. Hands-on exercises provide practical instruction to complement the explanations of principles, both of which make this a useful book for the classroom or self-study.' Bruce G. Buchanan, Emeritus Professor of Computer Science, University of Pittsburgh

Notă biografică


Descriere

Using robust software, this book focuses on learning assistants for evidence-based reasoning that learn complex problem solving from humans.