Phil Johnson-Laird's theory of mental models has proved to be an influential development in the cognitive sciences. This theory aims to provide a detailed account of both reasoning and inference on the one hand, and language on the other. It can therefore be regarded as a step toward the much-sought-after unified theory of cognition.; This book provides an overview of mental models research. Some of the contributors were collaborators or former graduate students of Johnson-Laird, and between them they cover the main strands of mental models theory. After an appreciation of Johnson-Laird, the book covers topics including language Processing, Reasoning, Inference, The Role Of Emotions, And The Impact Of mental illnesses on thought processes.
This book offers a unified theory of the major propertries of mind, including comprehension, inference, and consciousness. The author argues that we apprehend the world by building inner mental replicas of the relationships among objects and events that concern us. The mind is essentially a model-building device that can itself be modeled on a computer. The book provides a blueprint for building such a model and numberous important illustrations of how to do it.
"Cognitive psychology," "cognitive neuroscience," and "philosophy of mind" are names for three very different scientific fields, but they label aspects of the same scientific goal: to understand the nature of mental phenomena. Today, the three disciplines strongly overlap under the roof of the cognitive sciences. The book's purpose is to present views from the different disciplines on one of the central theories in cognitive science: the theory of mental models. Cognitive psychologists report their research on the representation and processing of mental models in human memory. Cognitive neuroscientists demonstrate how the brain processes visual and spatial mental models and which neural processes underlie visual and spatial thinking. Philosophers report their ideas about the role of mental models in relation to perception, emotion, representation, and intentionality. The single articles have different and mutually complementing goals: to introduce new empirical methods and approaches, to report new experimental results, and to locate competing approaches for their interpretation in the cross-disciplinary debate. The book is strongly interdisciplinary in character. It is especially addressed to researchers in any field related to mental models theory as both a reference book and an overview of present research on the topic in other disciplines. However, it is also an ideal reader for a specialized graduate course. Examines the theory of mental models from the perspectives of cognitive psychology, cognitive neuroscience and philosophy of the mind Introduces new empirical methods, experimental results, and interdisciplinary yet complementary approaches Serves as a reference book and an overview of current research
Phil Johnson-Laird's theory of mental models has proved to be an influential development in the cognitive sciences. This theory aims to provide a detailed account of both reasoning and inference on the one hand, and language on the other. It can therefore be regarded as a step toward the much-sought-after unified theory of cognition.; This book provides an overview of mental models research. Some of the contributors were collaborators or former graduate students of Johnson-Laird, and between them they cover the main strands of mental models theory. After an appreciation of Johnson-Laird, the book covers topics including language Processing, Reasoning, Inference, The Role Of Emotions, And The Impact Of mental illnesses on thought processes.
This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems. It is the first book specifically on visualization in science education. The book draws on the insights from cognitive psychology, science, and education, by experts from five countries. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages.
In a field choked with seemingly impenetrable jargon, Philip N. Johnson-Laird has done the impossible: written a book about how the mind works that requires no advance knowledge of artificial intelligence, neurophysiology, or psychology. The mind, he says, depends on the brain in the same way as the execution of a program of symbolic instructions depends on a computer, and can thus be understood by anyone willing to start with basic principles of computation and follow his step-by-step explanations. The author begins with a brief account of the history of psychology and the birth of cognitive science after World War II. He then describes clearly and simply the nature of symbols and the theory of computation, and follows with sections devoted to current computational models of how the mind carries out all its major tasks, including visual perception, learning, memory, the planning and control of actions, deductive and inductive reasoning, and the formation of new concepts and new ideas. Other sections discuss human communication, meaning, the progress that has been made in enabling computers to understand natural language, and finally the difficult problems of the conscious and unconscious mind, free will, needs and emotions, and self-awareness. In an envoi, the author responds to the critics of cognitive science and defends the computational view of the mind as an alternative to traditional dualism: cognitive science integrates mind and matter within the same explanatory framework. This first single-authored introduction to cognitive science will command the attention of students of cognitive science at all levels including psychologists, linguists, computer scientists, philosophers, and neuroscientists--as well as all readers curious about recent knowledge on how the mind works.
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.
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
What is cognitive science? The Foundations of Cognitive Science answers this question in a way that gives a feeling for the excitement, ferment, and accomplishments of this new field. It is the first broad treatment of cognitive science at an advanced level. Complete and authoritative, The Foundations of Cognitive Science covers the major architectures; provides background in philosophy linguistics, cognitive psychology, and neuroscience; and deals with methods for studying both brain and mind. All of the chapters have been written especially for the book by the leading scholars in the field. The foundations of cognitive science are developed in seven chapters covering computation, symbolic architectures, parallel distributed processing, grammars, semantics and formal logic, experimental cognitive science, and brain and cognition. These are then applied to the major cognitive domains of language acquisition, reading, discourse, mental models, categories and induction, problem solving, vision, visual attention, memory, action and motor control. The Foundations of Cognitive Science concludes with an assessment by a philosopher and a cognitive anthropologist. Michael I. Posner is Professor of Psychology at the University of Oregon. A Bradford Book. Contributors: Herbert A. SimonCraig A. KaplanZenon W. PylyshynAllen NewellJohn E. LairdPaul S. RosenbloomDavid E. RumelhartThomas WasowJon BarwiseJohn EtchemendyGordon H. BawerJohn P. ClapperTerrence J. SejnowskiPatricia Smith ChurchlandSteven PinkerAlexander PollatsekKeith RaynerBarbara J. GroszCandace L. SidnerMartha E. PollackP. N. Johnson-LairdEdward E. SmithKurt VanLehnEllen C. HildrethShimon UllmanAlan AllportDaniel L. SchacterDavid A. RosenbaumMichael I. JordanE. BizziF. A. Mussa IvaldiRoy D'AndradeGilbert Harman Contents: Computation, Symbolic Architectures, Parallel Distributed Processing, Grammars, Semantics and Formal Logic, Experimental Cognitive Science, Brain and Cognition, Language Acquisition, Reading, Discourse, Mental Models, Categories and Induction, Problem Solving, Vision, Visual Attention, Memory, Action, Motor Control, Culture, Philosophical Critique
Good reasoning can lead to success; bad reasoning can lead to catastrophe. Yet, it's not obvious how we reason, and why we make mistakes. This book looks at the mental processes that underlie our reasoning. It provides the most accessible account yet of the science of reasoning.
