Read more
This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of systems that use expert knowledge and reasoning to solve complex problems. It covers the main stages in the development of a knowledge-based system: understanding the application domain, modeling problem solving in that domain, developing the ontology and the reasoning rules, and testing the system. The book focuses on a special class of systems - learning assistants for evidence-based reasoning that learn complex problem solving expertise directly from human experts, support experts and non-experts 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 rapidly develop learning assistants in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cyber security, law, forensics, medicine, and education.
List of contents
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.
About the author
Gheorghe Tecuci (PhD, University of Paris-South and Polytechnic Institute of Bucharest) is Professor of Computer Science and Director of the Learning Agents Center at George Mason University, Virginia, Member of the Romanian Academy, and former Chair of Artificial Intelligence at the US Army War College. He has published 11 books and more than 190 papers.Dorin Marcu (PhD, George Mason University) is Research Assistant Professor in the Learning Agents Center at George Mason University, Virginia. He collaborated in the development of the Disciple Learning Agent Shell and a series of cognitive assistants based on it for different application domains, such as Disciple-COA (course of action critiquing), Disciple-COG (strategic center of gravity analysis), Disciple-LTA (learning, tutoring, and assistant), and Disciple-EBR (evidence-based reasoning).Mihai Boicu (PhD, George Mason University) is Associate Professor of Information Sciences and Technology and Associate Director of the Learning Agents Center at George Mason University, Virginia. He is the main software architect of the Disciple agent development platform and coordinated the software development of Disciple-EBR. He has received the IAAI Innovative Application Award.David A. Schum (PhD, Ohio State University) is Emeritus Professor of Systems Engineering, Operations Research, and Law, as well as Chief Scientist of the Learning Agents Center at George Mason University, Virginia. He has published more than 100 research papers and 6 books on evidence and probabilistic inference, and is recognized as one of the founding fathers of the emerging Science of Evidence.
Summary
This book presents a significant advancement in knowledge engineering based on learning agent technology. Using the software Disciple-EBR, students, practitioners, and researchers can rapidly develop learning assistants in numerous domains that require evidence-based reasoning, including cyber security, law, forensics, medicine, and education.
