Computer Models Of Mind

This book shows how computer models are used to study many psychological phenomena - including vision, language, reasoning, and learning.

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.

The human brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For more than a century, a diverse array of researchers searched for a language that could be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when the abstract world of mathematical modelling collides with the messy details of biology. Each chapter of Models of the Mind focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. In addition, Grace examines the history of the field, starting with experiments done on frog legs in the late eighteenth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. Throughout, she reveals the value of using the elegant language of mathematics to describe the machinery of neuroscience.

An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists. Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.

The basic questions addressed in this book are: what is the computational nature of cognition, and what role does it play in language and other mental processes?; What are the main characteristics of contemporary computational paradigms for describing cognition and how do they differ from each other?; What are the prospects for building cognition and how do they differ from each other?; and what are the prospects for building an artificial intelligence?

Computational approaches dominate contemporary cognitive science, promising a unified, scientific explanation of how the mind works. However, computational approaches raise major philosophical and scientific questions. In what sense is the mind computational? How do computational approaches explain perception, learning, and decision making? What kinds of challenges should computational approaches overcome to advance our understanding of mind, brain, and behaviour? The Routledge Handbook of the Computational Mind is an outstanding overview and exploration of these issues and the first philosophical collection of its kind. Comprising thirty-five chapters by an international team of contributors from different disciplines, the Handbook is organised into four parts: History and future prospects of computational approaches Types of computational approach Foundations and challenges of computational approaches Applications to specific parts of psychology. Essential reading for students and researchers in philosophy of mind, philosophy of psychology, and philosophy of science, The Routledge Handbook of the Computational Mind will also be of interest to those studying computational models in related subjects such as psychology, neuroscience, and computer science.

This work represents Dr. Jaki's rebuttal of contemporary claims about the existence of, or possibility for, man-made minds. His method includes a meticulously documtned survey of computer development, a review of the relevant results of brain research, and an evaluation of the accomplishments of physicalist schools in psychology, symbolic logic, and linguistics.