Intelligence Analysis as Discovery of Evidence, Hypotheses, and Arguments

Tecuci, Gheorghe|Schum, David A.|Marcu, Dorin

ISBN 10: 1107122600 / ISBN 13: 9781107122604

Published by CAMBRIDGE, 2016

About this Item

This book teaches the evidential and inferential issues involved in connecting the dots to draw defensible and persuasive conclusions from masses of evidence, providing a hands-on learning experience with an advanced analytical tool to generate and test h.

Seller Inventory # 132993343

Bibliographic Details

• Title: Intelligence Analysis as Discovery of Evidence, Hypotheses, and Arguments
• Publisher: CAMBRIDGE
• Publication Date: 2016
• Language: English
• ISBN 10: 1107122600
• ISBN 13: 9781107122604
• Binding: Gebunden
• Condition: New

About this title

Synopsis

This unique book on intelligence analysis covers several vital but often overlooked topics. It teaches the evidential and inferential issues involved in 'connecting the dots' to draw defensible and persuasive conclusions from masses of evidence: from observations we make, or questions we ask, we generate alternative hypotheses as explanations or answers; we make use of our hypotheses to generate new lines of inquiry and discover new evidence; and we test the hypotheses with the discovered evidence. To facilitate understanding of these issues and enable the performance of complex analyses, the book introduces an intelligent analytical tool, called Disciple-CD. Readers will practice with Disciple-CD and learn how to formulate hypotheses; develop arguments that reduce complex hypotheses to simpler ones; collect evidence to evaluate the simplest hypotheses; and assess the relevance and the believability of evidence, which combine in complex ways to determine its inferential force and the probabilities of the hypotheses.

About the Authors

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 eleven books and more than 190 papers.

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 one hundred research papers and six books on evidence and probabilistic inference, and is recognized as one of the founding fathers of the emerging Science of Evidence.

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.