Traces the relationship between the development of computing machines and our knowledge of brain functioning, and introduces corresponding mathematical models designed to describe this relationship. Begins with a historical overview tracing the rise of cybernetics to the current interchange of ideas between AI and brain theory. Subsequent chapters introduce neural sets and finite automata, the crucial cybernetic concepts of feedback and realization, pattern recognition networks, "semi-neural" learning networks, capabilities of Turing machines and automata which construct as well as compute. The final chapter presents two accessible proofs of Gödel's Incompleteness Theorem.

Brains, Machines, and Mathematics.

Computers & Technology

Arbib, Michael A.

Computer Science

McGraw-Hill Book Company

Computers and the cybernetic society

Science & Math

Mathematics

Academic Press

Computers and the Cybernetic Society

This book attempts to build up sufficient perspective on category theory without demanding more of the reader than a basic knowledge of sets and matrix theory.

Arrows, Structures, and Functors: The Categorical Imperative

Academic Pr

Theories of Abstract Automata (Automatic Computation)

Theories of abstract automata (Prentice-Hall series in automatic computation)

Prentice-Hall Press

After decades of research on minds and brains and a decade of conversations with architects, Michael Arbib presents When Brains Meet Buildings as an invitation to the science behind architecture, richly illustrated with buildings both famous and domestic. As he converses with the reader, he presents action-oriented perception, memory, and imagination as well as atmosphere, aesthetics, and emotion as keys to analyzing the experience and design of architecture. He also explores what it might mean for buildings to have "brains" and illuminates all this with an appreciation of the biological and cultural evolution that supports the diverse modes of human living that we know today. These conversations will not only raise the level of interaction between architecture and neuroscience but, by explaining the world of each group to the other, will also engage all readers who share a fascination with both the brains within them and the buildings around them. Michael Arbib is a pioneer in the interdisciplinary study of computers and brains and has long studied brain mechanisms underlying the visual control of action. His expertise makes him a unique authority on the intersection of architecture and neuroscience.

When Brains Meet Buildings

Arts & Photography

Architecture

Oxford University Press

Bringing together the perspectives of neurophysiology, cognitive psychology, and artificial intelligence, this book introduces a new approach to the study of language. The authors propose schema theory as a unifying perspective in cognitive science and use three models to illustrate their argument: a study of sentence understanding applied to the analysis of data on aphasia; a "computational neo-Piagetian" approach to language acquisition in a two-year-old; and a model of how people describe visual scenes. The final chapter charts the value of the schema-theoretic approach to computational linguistics in particular and cognitive science in general as part of the search for commonalities between the representations and processes employed in linguistic and other cognitive domains.

From Schema Theory to Language

Conklin, E. Jeffrey

Hill, Jane C.

Unlike any other species, humans can learn and use language. This book explains how the brain evolved to make language possible, through what Michael Arbib calls the Mirror System Hypothesis. Because of mirror neurons, monkeys, chimps, and humans can learn by imitation, but only "complex imitation," which humans exhibit, is powerful enough to support the breakthrough to language. This theory provides a path from the openness of manual gesture, which we share with nonhuman primates, through the complex imitation of manual skills, pantomime, protosign (communication based on conventionalized manual gestures), and finally to protospeech. The theory explains why we humans are as capable of learning sign languages as we are of learning to speak. This fascinating book shows how cultural evolution took over from biological evolution for the transition from protolanguage to fully fledged languages. The author explains how the brain mechanisms that made the original emergence of languages possible, perhaps 100,000 years ago, are still operative today in the way children acquire language, in the way that new sign languages have emerged in recent decades, and in the historical processes of language change on a time scale from decades to centuries. Though the subject is complex, this book is highly readable, providing all the necessary background in primatology, neuroscience, and linguistics to make the book accessible to a general audience.

How the Brain Got Language: The Mirror System Hypothesis (Oxford Studies in the Evolution of Language)

Health, Fitness & Dieting

Psychology & Counseling

These nineteen original essays present current developments in the exciting field of vision research, stressing contributions from neurophysiology, psychophysics, and computer science. They are unified by the theme of how best to structure the computations for visual systems and are placed in perspective by a major integrative essay provided by the editors. Broad in scope and packed with useful detail, Vision, Brain, and Cooperative Computation covers the entire range of perceptual experience from sensors to learning. Crossing several traditional disciplinary boundaries, it offers valuable insights into artificial intelligence and cognitive science with diverse and timely essays on visual neurophysiology, visual psychophysics, machine vision and robotics, and connectionism and cooperative computation. Michael A. Arbib is Professor of Computer Science, Neurobiology, and Physiology at the University of Southern California. Allen R. Hanson is an Associate Professor in the Department of Computer and Information Science at the University of Massachusetts in Amherst. Vision, Brain, and Cooperative Computation is included in the series Computational Models of Cognition and Perception, edited by Jerome A. Feldman, Patrick J. Hayes, and David E. Rumelhart. A Bradford Book.

Vision, Brain, and Cooperative Computation (Computational Models of Cognition and Perception)

National Institutes of Health (U. S.)

Hanson, Allen R.

Alfre

Software

MIT Press]

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Books by Arbib, Michael A.