Synopses & Reviews
The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling it in more complex, realistic environments, such as those studied by researchers in the field of human factors. The problems that the cognitive modeling community is tackling focus on modeling certain problems of communication and control that arise when integrating with the external environment factors such as implicit and explicit knowledge, emotion, cognition, and the cognitive system. These problems must be solved in order to produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting the results of these functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of theories of control: Type 1 theories of the structure, functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, including how and what they communicate to the controller. This book presents the current state of the art for both types of theories, as well as contrasts among current approaches to human-performance models. It will be an important resource for professional and student researchers in cognitive science, cognitive-engineering, and human-factors.
Contributors: Kevin A. Gluck, Jerry T. Ball, Michael A. Krusmark, Richard W. Pew, Chris R. Sims, Vladislav D. Veksler, John R. Anderson, Ron Sun, Nicholas L. Cassimatis, Randy J. Brou, Andrew D. Egerton, Stephanie M. Doane, Christopher W. Myers, Hansjörg Neth, Jeremy M Wolfe, Marc Pomplun, Ronald A. Rensink, Hansjörg Neth, Chris R. Sims, Peter M. Todd, Lael J. Schooler, Wai-Tat Fu, Michael C. Mozer, Sachiko Kinoshita, Michael Shettel, Alex Kirlik, Vladislav D. Veksler, Michael J. Schoelles, Jerome R. Busemeyer, Eric Dimperio, Ryan K. Jessup, Jonathan Gratch, Stacy Marsella, Glenn Gunzelmann, Kevin A. Gluck, Scott Price, Hans P. A. Van Dongen, David F. Dinges, Frank E. Ritter, Andrew L. Reifers, Laura Cousino Klein, Michael J. Schoelles, Eva Hudlicka, Hansjörg Neth, Christopher W. Myers, Dana Ballard, Nathan Sprague, Laurence T. Maloney, Julia Trommershäuser, Michael S. Landy, A. Hornof, Michael J. Schoelles, David Kieras, Dario D. Salvucci, Niels Taatgen, Erik M. Altmann, Richard A. Carlson, Andrew Howes, Richard L. Lewis, Alonso Vera, Richard P. Cooper, and Michael D. Byrne
"At a time when neuroscience attempts to localize cognitive processes inside the head, cognitive science finally looks outside the mind for an integrated view of cognition. The essays in this significant and fascinating book focus on the computational modeling of the interaction between mind and environment. A stimulating, comprehensive set of readings composed by excellent researchers." --Gerd Gigerenzer, Director, Max Planck Institute for Human Development, Berlin
"This volume provides insight into the current and enduring tensions among the research communities attempting to understand human performance and the cognitive functions underlying it . . ." --Susan F. Chipman, Manager, Cognitive Science Program at the U.S. Office of Naval Research
"This book reveals the great progress being made in the field of cognitive science . . . The current volume brings together the best and brightest of mathematical modelers with those computational cognitive modelers whose focus is on integrated cognitive systems; the results show the state of the art, and point the way toward exciting future progress." --Richard M. Shiffrin, Luther Dana Waterman Professor of Psychology, Indiana University
"A must-read for students of the human mind. A whos who in cognitive science describes the systems approach to understanding for practitioners not just of psychology but of computer science, artificial intelligence, and neural science." --John Tangney
". . . [Gray] has provided a valuable framework in which models can be accommodated and integrated with a diversity ranging from those of the unmanned air vehicle operator or highway driver to those addressing the millisecond timing of attention switching. . . . The volume also does an admirable job in bringing applied researchers together with those interested in more basic cognitive phenomena, in a way that equally serves the interests of applications, and of advancing the fundamental theory of how the brain performs operations of perception, problem solving, action selection and task management." --Christopher D. Wickens, Senior Scientist, Alion Science and Technology MA&D Operation
The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling cognition in more complex, realistic environments, such as those studied by researchers in the field of human-fators. The problems that
the human-factors community is tackling focus on modeling certain problems of communication and control that arise in the integration of implicit and explicit knowledge, emotion, and cognition, and the cognitive system with the external environment. These problems must be addressed in order to
produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting
the results of functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of tehories of control: Type 1 theories of the structure,
functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, how, and what they communicate to the controller. This volume presents, for both types of theories, the current state of the art, as well as contrasts among current approaches to
human-performance models. Contributors include Richard Pew, John Anderson, Dana Ballard, Laurence Maloney, Jeremy Wolf, Frank Ritter, Richard Cooper, Ronald Rensink, Mike Byrne, Jerome Busemeyer, Eve Hudlincka, Dave Kieras, Rich Carlson, Mike Mozer, Alex Kirlik, and Peter Todd. The book will be an
important resource for the cognitive-science community, the cognitive-engineering community, and the human-factors community.
About the Author
Wayne D. Gray
is a researcher in the fields of computational cognitive modeling, interactive behavior, cognitive task analysis, cognitive workload, and human error. Since earning his Ph.D. from U. C. Berkeley he has worked for both government and industry laboratories, as well as universities. He is currently a Professor of Cognitive Science at Rensselaer Polytechnic Institute. Dr. Gray is a past Chair of the Cognitive Science Society and the founding Chair of the Human Performance Modeling technical group of the Human Factor and Ergonomics Society.
Table of Contents
Section I: Beginnings.
1. Composition and Control of Integrated Cognitive Systems, Wayne D. Gray
2. Cognitive Control in a Computational Model of the Predator Pilot, Kevin A. Gluck, Jerry T. Ball, and Michael A. Krusmark
3. Some History of Human Performance Modeling, Richard W. Pew
Section II: Systems.
Introduction: Systems-level theories in computational cognitive modeling. Chris R. Sims and Vladislav D. Veksler
4. Using Brain Imaging to Guide the Development of a Cognitive Architecture, John R. Anderson
5. The Motivational and Metacognitive Control in CLARION, Ron Sun
6. Reasoning as Cognitive Self-Regulation, Nicholas L. Cassimatis
7. Construction/Integration Architecture: Dynamic Adaptation to Task Constraints, Randy J. Brou, Andrew D. Egerton, and Stephanie M. Doane
Section III: Visual Attention and Perception. Christopher W. Myers and Hansjörg Neth
8. Guided Search 4.0: Current Progress with a model of visual search, Jeremy M. Wolfe
9. Advancing Area Activation towards a General Model of Eye Movements in Visual Search, Marc Pomplun
10. The Modeling and Control of Visual Perception, Ronald A. Rensink
Section IV: Task Environment.
Introduction: Environmental Constraints on Integrated Cognitive Systems. Hansjörg Neth and Chris R. Sims
11. From disintegrated architectures of cognition to an integrated heuristic toolbox, Peter M. Todd and Lael J. Schooler
12. A Rational-Ecological Approach to the Exploration-Exploitation Tradeoffs: Bounded Rationality and Suboptimal Performance, Wai-Tat Fu
13. Sequential dependencies in human behavior offer insights into cognitive control, Michael C. Mozer, Sachiko Kinoshita, and Michael Shettel
14. Ecological Resources for Modeling Interactive Behavior and Embedded Cognition, Alex Kirlik
Section V: Emotion.