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The Brain from 25,000 Feet - High Level Explorations of Brain Complexity, Perception, Induction and Vagueness (Hardcover, 2003... The Brain from 25,000 Feet - High Level Explorations of Brain Complexity, Perception, Induction and Vagueness (Hardcover, 2003 ed.)
Mark A. Changizi
R4,620 Discovery Miles 46 200 Ships in 12 - 17 working days

In The Brain from 25,000 Feet, Mark A. Changizi defends a non-reductionist philosophy and applies it to a variety of problems in the brain sciences. Some of the key questions answered are as follows. Why do we see visual illusions, and why are illusions inevitable for any finite-speed vision machine? Why aren't brains universal learning machines, and what does the riddle of induction and its solution have to do with human learning and innateness? The author tackles such questions as why the brain is folded, and why animals have as many limbs as they do, explaining how these relate to principles of network optimality. He describes how most natural language words are vague and then goes on to explain the connection to the ultimate computational limits on machines. There is also a fascinating discussion of how animals accommodate greater behavioral complexity. This book is a must-read for researchers interested in taking a high-level, non-mechanistic approach to answering age-old fundamental questions in the brain sciences.

The Brain from 25,000 Feet - High Level Explorations of Brain Complexity, Perception, Induction and Vagueness (Paperback,... The Brain from 25,000 Feet - High Level Explorations of Brain Complexity, Perception, Induction and Vagueness (Paperback, Softcover reprint of hardcover 1st ed. 2003)
Mark A. Changizi
R4,262 Discovery Miles 42 620 Out of stock

In The Brain from 25,000 Feet, Mark A. Changizi defends a non-reductionist philosophy and applies it to a variety of problems in the brain sciences. Some of the key questions answered are as follows. Why do we see visual illusions, and why are illusions inevitable for any finite-speed vision machine? Why aren't brains universal learning machines, and what does the riddle of induction and its solution have to do with human learning and innateness? The author tackles such questions as why the brain is folded, and why animals have as many limbs as they do, explaining how these relate to principles of network optimality. He describes how most natural language words are vague and then goes on to explain the connection to the ultimate computational limits on machines. There is also a fascinating discussion of how animals accommodate greater behavioral complexity. This book is a must-read for researchers interested in taking a high-level, non-mechanistic approach to answering age-old fundamental questions in the brain sciences.

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