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Natural and artificial intelligence : misconceptions about brains and neural networks /
How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal or...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; New York :
North-Holland,
1992.
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| Edición: | New, expanded edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Callata�y, Armand M. de, |d 1935- |e author. | |
| 245 | 1 | 0 | |a Natural and artificial intelligence : |b misconceptions about brains and neural networks / |c Armand M. de Callatay. |
| 250 | |a New, expanded edition. | ||
| 264 | 1 | |a Amsterdam ; |a New York : |b North-Holland, |c 1992. | |
| 300 | |a 1 online resource (P1-P156, 560 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references (pages 509-536) and index. | ||
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| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2010. |5 MiAaHDL | ||
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| 588 | 0 | |a Print version record. | |
| 520 | |a How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal organelles. These transformations are approximately abstracted as all-or-none operations. Thus the computer-like neural systems become plausible biological models. This illustrated book shows how artificial animals with such brains learn invariant methods of behavior control from their repeated actions. These robots can make decisions in any circumstances and reason by analogy whenever possible. | ||
| 505 | 0 | |a Front Cover; Natural and Artificial Intelligence: Misconceptions about Brains and Neural Networks; Copyright Page; How to Read the Book; Summary of the Expanded Sections; Summary of the Book (1986); Table of Contents; LIST OF ILLUSTRATIONS; PROLOGUE; 1. Misconceptions about Brain Principles; Are computers brain models?; Should thought depend on an unifying principle?; Should brains be first studied by reductionist methods?; Should neural networks be homogenous?; Are symbolic models a useless return to mental ideas?; Is logic useful in brains?; Can logical reasoning be false? | |
| 505 | 8 | |a Do brains abstract what they process?Must logic be ""neat"" or not exist?; Are artificial intelligence and neural networks incompatible?; Are simple models always better?; Can neural networks be controlled by clocks?; Is mass action functionally different from centralized control?; Are our behaviors perturbed by noise?; 2. Misconceptions about Neural Networks; Do researchers agree on a definition of ""neural networks""?; Are neural networks new systems?; Are neural networks useful only for noisy data?; Can neural networks only compute likelihood? | |
| 505 | 8 | |a Can noise be filtered out in symbolic systems?Can errors be suppressed when learning is irreversible?; Do we actively avoid repeating wrong decisions?; Is the plasticity of neural maps used for learning?; Is learning a transformation of memory?; Should cognitivism be 'neat'?; Are circular NNs similar to attractor NNs?; Are grand-mother neurons impossible?; Can dense patterns be processed in a neural group?; Can memory be made sparse?; Should feature extractors learn?; Why are latches useful?; Are working hypotheses useful?; Is document retrieval a complex algorithm? | |
| 505 | 8 | |a Is distributed more reliable than redundant?Is large capacity opposed to robustness?; Can learning by backpropagation be used in brains?; Should memory be assigned?; Can captor values be used in NNs?; Is topographical organization useful everywhere?; 3. Misconceptions about Brains; Should NNs be called NNNs?; Are all-or-none switches biologically impossible?; Can memory persist in biological organisms?; Can one reliably reason with many false memories?; Can repetition stabilize memory?; Can rehearsal stabilize memory?; Can homeostasis stabilize memory? | |
| 505 | 8 | |a Do neuronal impulses play the role of computer states?Can a weighted sum be computed by a calcium impulse?; Is impulse sparseness not observed in brains?; Do local axons have action potentials?; Can diffusion in the axon of chandelier cells be significant?; Are waking brains desynchronized?; Are oscillations needed for synchronization?; Is the normal behavior of neuronal networks oscillatory?; Is processing in steps seen as oscillations?; Do computer programs have slow rhythms?; Can brain computations be disordered?; Are neurons using only excitation and inhibition? | |
| 546 | |a English. | ||
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Brain |x Physiology. | |
| 650 | 2 | |a Artificial Intelligence |0 (DNLM)D001185 | |
| 650 | 2 | |a Brain |x physiology |0 (DNLM)D001921Q000502 | |
| 650 | 2 | |a Models, Neurological |0 (DNLM)D008959 | |
| 650 | 2 | |a Neural Networks, Computer |0 (DNLM)D016571 | |
| 650 | 6 | |a R�eseaux neuronaux (Informatique) |0 (CaQQLa)201-0209597 | |
| 650 | 6 | |a Intelligence artificielle. |0 (CaQQLa)201-0008626 | |
| 650 | 6 | |a Cerveau |0 (CaQQLa)201-0003439 |x Physiologie. |0 (CaQQLa)201-0380273 | |
| 650 | 7 | |a artificial intelligence. |2 aat |0 (CStmoGRI)aat300251574 | |
| 650 | 7 | |a COMPUTERS |x General. |2 bisacsh | |
| 650 | 7 | |a Artificial intelligence. |2 fast |0 (OCoLC)fst00817247 | |
| 650 | 7 | |a Brain |x Physiology. |2 fast |0 (OCoLC)fst00837651 | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast |0 (OCoLC)fst01036260 | |
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| 653 | 0 | |a Artificial intelligence |a Related to |a Mind | |
| 776 | 0 | 8 | |i Print version: |a Callata�y, Armand M. de, 1935- |t Natural and artificial intelligence. |b New, expanded ed. |d Amsterdam ; New York : North-Holland, 1992 |w (DLC) 92012713 |w (OCoLC)25630434 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780444890818 |z Texto completo |