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Intelligence Analysis as Discovery of Evidence, Hypotheses, and Arguments
Connecting the Dots

$56.00 ( ) USD

  • Date Published: August 2016
  • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • format: Adobe eBook Reader
  • isbn: 9781316655597

$ 56.00 USD ( )
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About the Authors
  • 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.

    • Covers several vital topics that are overlooked in other works
    • Follows a hands-on approach to learning intelligence analysis
    • Provides an advanced analytical tool, Disciple-CD, for complex evidence-based hypothesis analysis
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    Reviews & endorsements

    "Intelligence Analysis as Discovery of Evidence, Hypotheses, and Arguments is a valuable resource for those interested in improving intelligence analysis. It provides both prospective and current intelligence analysts with an easy to read and understand explanation of a complex process, along with suggestions for how to more effectively implement that process. The examples from intelligence analysis and comparison to similar practices in other fields such as medicine, law, and law enforcement help the reader better understand how the interplay of evidence, hypotheses and arguments can develop in different contexts. In that sense, this book provides a wonderful platform for improving intelligence analysis by learning and employing best scientific reasoning practices."
    Stephen Marrin, James Madison University, Virginia

    "This is an important work in several ways. The authors both help readers learn the basics and give advanced training in the craft of analytical reasoning by providing sophisticated tools to guide understanding of its strengths, its probabilistic nature, and its limitations. "Deep" learning is what distinguishes experts from gifted amateurs; this book will help amateurs develop expert habits through guided learning and practice. I would not only recommend this book for students of intelligence, but also for students of law, journalism, and national security. The first several chapters should be mandatory reading for 'customers' and critics of intelligence, including policymakers, legislators, and professional journalists who are quick to ask "why didn’t you connect the dots?" while they themselves probably have no idea how difficult that may be."
    Mark T. Clark, Director, National Security Studies, California State University, San Bernardino, and President, Association for the Study of Middle East and Africa (ASMEA)

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    Product details

    • Date Published: August 2016
    • format: Adobe eBook Reader
    • isbn: 9781316655597
    • contains: 111 colour illus. 23 tables
    • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • Table of Contents

    1. Intelligence analysis: 'connecting the dots'
    2. Marshaling thoughts and evidence for imaginative analysis
    3. Disciple-CD: a cognitive assistant for connecting the dots
    4. Evidence
    5. Divide and conquer: a necessary approach to complex analysis
    6. Assessing the believability of evidence
    7. Chains of custody
    8. Recurrent substance-blind combinations of evidence
    9. Major sources of uncertainty in masses of evidence
    10. Assessing and reporting uncertainty: some alternative methods
    11. Analytic bias
    12. Learning and reusing analytic expertise: beyond Disciple-CD.

  • Resources for

    Intelligence Analysis as Discovery of Evidence, Hypotheses, and Arguments

    Gheorghe Tecuci, David A. Schum, Dorin Marcu, Mihai Boicu

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  • Authors

    Gheorghe Tecuci, George Mason University, Virginia
    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, George Mason University, Virginia
    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, George Mason University, Virginia
    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, George Mason University, Virginia
    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.

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