So how do you actually engineer knowledge to integrate into an assistant system? Its a mix of knowledge architecture, reasoning and effective delivery. Many of our early attempts struggled with the idea. This book takes a look at approaches. I will be reviewing. From GMU.
Knowledge Engineering: Building Cognitive Assistants for Evidence-based Reasoning Authors: Gheorghe Tecuci, Dorin Marcu, Mihai Boicu, David A. Schum
Hardcover: 456 pages
Publisher: Cambridge University Press (September 2016)
ISBN: 9781107122567
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. .... "
Discussion in Cognitive Systems Institute, Linkedin.
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