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.

'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

• 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.

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.

'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

• 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.

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.

'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

• 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.