Responding to an explosion of new mathematical and computational models used in the fields of cognitive science, this book provides simple tutorials concerning the development and testing of such models. The authors focus on a few key models, with a primary goal of equipping readers with the fundamental principles, methods, and tools necessary for evaluating and testing any type of model encountered in the field of cognitive science.

The work of Richard M. Shiffrin has highly impacted the field of cognitive science, and current developments within perception and memory have been influenced by his ideas. In this volume, several key figures in the field will comment on these developments and put them in a wider perspective. Although many theories and models have been presented in recent years for various aspects of human cognition, there have not been many comparative evaluations that focus on how these models have really advanced our understanding of the underlying mechanisms. This volume will be a valuable source of information for both cognitive scientists working in the field, and researchers and students looking for a clear, accessible presentation of the key problems in cognitive science. Highlighted sections include attention and perception, memory functions and processes, knowledge representation and semantics, modelling approaches and applications.

Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.

These essays tackle some of the central issues in visual cognition, presenting experimental techniques from cognitive psychology, new ways of modeling cognitive processes on computers from artificial intelligence, and new ways of studying brain organization from neuropsychology, to address such questions as: How do we recognize objects in front of us? How do we reason about objects when they are absent and only in memory? How do we conceptualize the three dimensions of space? Do different people do these things in different ways? And where are these abilities located in the brain? While this research, which appeared as a special issue of the journal Cognition, is at the cutting edge of cognitive science, it does not assume a highly technical background on the part of readers. The book begins with a tutorial introduction by the editor, making it suitable for specialists and nonspecialists alike.

A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.

The emerging interdisciplinary field of cognitive choice models integrates theory and recent research findings from both decision process and choice behavior. Cognitive decision processes provide the interface between the environment and brain, enabling choice behavior, and the basic cognitive mechanisms underlying decision processes are fundamental to all fields of human activity. Yet cognitive processes and choice processes are often studied separately, whether by decision theorists, consumer researchers, or social scientists. In Cognitive Choice Modeling, Zheng Joyce Wang and Jerome R. Busemeyer introduce a new cognitive modeling approach to the study of human choice behavior. Integrating recent research findings from both cognitive science and choice behavior, they lay the groundwork for the emerging interdisciplinary field of cognitive choice modeling.

Much of our behavior is guided by our understanding of events. We perceive events when we observe the world unfolding around us, participate in events when we act on the world, simulate events that we hear or read about, and use our knowledge of events to solve problems. In this book, Gabriel A. Radvansky and Jeffrey M. Zacks provide the first integrated framework for event cognition and attempt to synthesize the available psychological and neuroscience data surrounding it. This synthesis leads to new proposals about several traditional areas in psychology and neuroscience including perception, attention, language understanding, memory, and problem solving. Radvansky and Zacks have written this book with a diverse readership in mind. It is intended for a range of researchers working within cognitive science including psychology, neuroscience, computer science, philosophy, anthropology, and education. Readers curious about events more generally such as those working in literature, film theory, and history will also find it of interest.

Demystify the core concepts of cognitive psychology Written specifically for psychology students – and not other academics - Cognitive Psychology For Dummies is an accessible and entertaining introduction to the field. Unlike the dense and jargon-laden content found in most psychology textbooks, this practical guide provides readers with easy-to-understand explanations of the fundamental elements of cognitive psychology so that they are able obtain a firm grasp of the material. Cognitive Psychology For Dummies follows the structure of a typical university course, which makes it the perfect supplement for students in need of a clear and enjoyable overview of the topic. The complexities of a field that explores internal mental processes – including the study of how people perceive, remember, think, speak, and solve problems – can be overwhelming for first-year psychology students. This practical resource cuts through the academic-speak to provide a clear understanding of the most important elements of cognitive psychology. Obtain a practical understanding of the core concepts of cognitive psychology Supplement required course reading with clear and easy-to-understand overviews Gain confidence in your ability to apply your knowledge of cognitive psychology Prepare for upcoming exams or topic discussions Cognitive Psychology For Dummies is the perfect resource for psychology students who need a clear and readable overview of the core concepts of cognitive psychology.

An accessible introduction to the principles of computational and mathematical modeling in psychology and cognitive science This practical and readable work provides students and researchers, who are new to cognitive modeling, with the background and core knowledge they need to interpret published reports, and develop and apply models of their own. The book is structured to help readers understand the logic of individual component techniques and their relationships to each other.