Free PDF An Introduction to Natural Computation (Complex Adaptive Systems), by Dana H. Ballard
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An Introduction to Natural Computation (Complex Adaptive Systems), by Dana H. Ballard
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It is now clear that the brain is unlikely to be understood without recourse to computational theories. The theme of An Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently been extended in ways that make them useful for describing the brain's programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It stresses the broad spectrum of learning models -- ranging from neural network learning through reinforcement learning to genetic learning -- and situates the various models in their appropriate neural context.To write about models of the brain before the brain is fully understood is a delicate matter. Very detailed models of the neural circuitry risk losing track of the task the brain is trying to solve. At the other extreme, models that represent cognitive constructs can be so abstract that they lose all relationship to neurobiology. An Introduction to Natural Computation takes the middle ground and stresses the computational task while staying near the neurobiology.
- Sales Rank: #2066376 in Books
- Published on: 1997-04
- Original language: English
- Number of items: 1
- Dimensions: 10.25" h x 7.25" w x .75" l,
- Binding: Hardcover
- 307 pages
Review
This is a wonderful book that brings together in one place the modern view of computation as found in nature. It is well written and has soemthing or everyone from the undergraduate to the advanced researcher.
(Terrence J. Sejnowski, Howard Hughes Medical Institute at The Salk Institute for Biological Studies, La Jolla, California)Ballard's text offers clear, direct introductions to the key tools and concepts needed in contemporary approached to AI, including state spaces, dynamics, memory models, reinforcement learning, and evolutionary algorithms. All contribute to the book's central aim: to undestand the computations that permit the survival and successful adaptive behavior of natural systems.
(Stewart W. Wilson, International Society for Adaptive Behavior, and The Rowland Institute for Science)Ballard has writtena a lucid introductory text covering a collection of material that is unusual by present standards but that is likely to form an indispensible core of future advances in what Ballard calls natural computation. The great activity over the last decade in biologically-related computation has overrun some of the old disciplinary boundaries, leaving uncertainty as to what one should know to appreciate-- as well as to participate-- in this active research area. Ballard introduces a collection of topics that would be hard to access without taking a half dozen courses in computer science, applied mathematics, and systems engineering. He shows how these topics all participate in a unified and original view of natural computation. If I had access to this book whn my interest in natural computation was aroused as an undergraduate, it would have saved me a lot of time. I envy today's students chance to study, in one course, this collection of essential material.
(Andy Barto, Professor of Computer Science, University of Massechusetts at Amherst)An Introduction to Natural Computation could seve as an introductory textbook for undergraduate courses surveying computational aspects of biological systems. It covers a lot of important topics in this area. Ballard is an excellent researcher with a broad, powerful view.
(Richard Sutton, Senior Research Scientist, Department of Computer Science, University of Massechusetts)I am EXTREMELY enthusiastic about this work. This is the first such book I've seeb that comes even close to covering the topic. I'd love to use it for teahing.
(Alex (Sandy) Pentland, Academic Head, The Media Lab, M.I.T. Toshiba Professor of Media Arts and Sciences) About the Author
Dana H. Ballard is Professor of Computer Science at the University of Texas at Austin.
Most helpful customer reviews
11 of 12 people found the following review helpful.
From Caltech
By James P. Turpin
This book is one of the two main books used in Caltech's Neural Computation class (the other is Introduction to the Theory of Neural Computation by Hertz, Krogh, and Palmer). This book covers a wider spectrum of learning models than most books, including Hertz, et al. It is still fairly mathematically rigorous, although not as much as Hertz, et al. It is ideal for somebody who wants a fairly mathematically rigorous description of the subject, but also wants something more comprehensive than Herts, et al.
6 of 6 people found the following review helpful.
Very informative - but you'll need an icepack for your head
By David A. Bayliss
Fifteen years ago I did research in this area and had just completed a math degree. I thought it would be interesting to get back up to speed.
I found the book fascinating, tremendous work has been done in this field and this is a good broad treatment of it. For anyone who is into computer science but has never studied the brain it will be a tremendous eye opener.
But boy, was it hard work. I found I had to read & re-read sections just to understand some of the math involved. In fairness the book does cover everything you need but if you have never done college level math, or you have forgotten most of it, then don't tackle this book when you are tired!
0 of 1 people found the following review helpful.
The book is well-written and provides a good overview of the field
By Ralph K. Cavin, III
The book is well-written and provides a good overview of the field. I don't think it breaks new ground in natural computation but rather is designed as a textbook to introduce the field.
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