Adversarial reasoning : computational approaches to reading the opponent's mind / edited by Alexander W. Kott, William M. McEneaney

Includes bibliographical references and index

About the authors -- 1.1. Adversarial models for opponent intent inferencing / Eugene Santos Jr. and Qunhua Zhao -- 1.2. Human factors in opponent intent / Paul E. Nielsen, Jacob Crossman, and Randolph M. Jones -- 1.3. Extrapolation of the opponent's past behaviors / Sven A. Brueckner and H. Van Dyke Parunak -- 1.4. Plan recognition / Christopher Geib -- 2.1. Detecting deception / Christopher Elsaesser and Frank J. Stech -- 2.2. Deception as a semantic attack / Paul Thompson -- 2.3. Application and value of deception / Joao Pedro Hespanha -- 2.4. Robustness against deception / William M. McEneaney and Rajdeep Singh -- 3.1. The role of imperfect information / Austin Parker, Dana Nau, and V. S. Subrahmanian -- 3.2. Handling partial and corrupted information / Ashitosh Swarup and Jason L. Speyer -- 3.3. Strategies in large-scale problems / Boris Stilman, Vladimir Yakhnis, and Oleg Umanskiy -- 3.4 Learning to strategize / Gregory Calbert -- 3.5. Learning from and about the opponent / Pu Huang and Katia Sycara

Featuring approaches that draw from disciplines such as artificial intelligence and cognitive modeling, this book describes technologies and applications that address a broad range of practical problems, including military planning and command, military and foreign intelligence, antiterrorism and domestic security, as well as simulation and training systems. The authors present an overview of each problem and then discuss approaches and applications, combining theoretical rigor with accessibility. This comprehensive volume covers intent and plan recognition, deception discovery, and strategy formulation