A nonclassical symbolic theory of working memory, mental computations, and mental set
The paper tackles four basic questions associated with human brain as a learning system. How can the brain learn to (1) mentally simulate different external memory aids, (2) perform, in principle, any mental computations using imaginary memory aids, (3) recall the real sensory and motor events and s...
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ftdatacite:10.48550/arxiv.0901.1152 2023-05-15T18:32:43+02:00 A nonclassical symbolic theory of working memory, mental computations, and mental set Eliashberg, Victor 2009 https://dx.doi.org/10.48550/arxiv.0901.1152 https://arxiv.org/abs/0901.1152 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Artificial Intelligence cs.AI Neural and Evolutionary Computing cs.NE FOS Computer and information sciences Preprint Article article CreativeWork 2009 ftdatacite https://doi.org/10.48550/arxiv.0901.1152 2022-04-01T15:13:49Z The paper tackles four basic questions associated with human brain as a learning system. How can the brain learn to (1) mentally simulate different external memory aids, (2) perform, in principle, any mental computations using imaginary memory aids, (3) recall the real sensory and motor events and synthesize a combinatorial number of imaginary events, (4) dynamically change its mental set to match a combinatorial number of contexts? We propose a uniform answer to (1)-(4) based on the general postulate that the human neocortex processes symbolic information in a "nonclassical" way. Instead of manipulating symbols in a read/write memory, as the classical symbolic systems do, it manipulates the states of dynamical memory representing different temporary attributes of immovable symbolic structures stored in a long-term memory. The approach is formalized as the concept of E-machine. Intuitively, an E-machine is a system that deals mainly with characteristic functions representing subsets of memory pointers rather than the pointers themselves. This nonclassical symbolic paradigm is Turing universal, and, unlike the classical one, is efficiently implementable in homogeneous neural networks with temporal modulation topologically resembling that of the neocortex. : 29 pages, 7 figures Report The Pointers DataCite Metadata Store (German National Library of Science and Technology) |
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Artificial Intelligence cs.AI Neural and Evolutionary Computing cs.NE FOS Computer and information sciences |
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Artificial Intelligence cs.AI Neural and Evolutionary Computing cs.NE FOS Computer and information sciences Eliashberg, Victor A nonclassical symbolic theory of working memory, mental computations, and mental set |
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Artificial Intelligence cs.AI Neural and Evolutionary Computing cs.NE FOS Computer and information sciences |
description |
The paper tackles four basic questions associated with human brain as a learning system. How can the brain learn to (1) mentally simulate different external memory aids, (2) perform, in principle, any mental computations using imaginary memory aids, (3) recall the real sensory and motor events and synthesize a combinatorial number of imaginary events, (4) dynamically change its mental set to match a combinatorial number of contexts? We propose a uniform answer to (1)-(4) based on the general postulate that the human neocortex processes symbolic information in a "nonclassical" way. Instead of manipulating symbols in a read/write memory, as the classical symbolic systems do, it manipulates the states of dynamical memory representing different temporary attributes of immovable symbolic structures stored in a long-term memory. The approach is formalized as the concept of E-machine. Intuitively, an E-machine is a system that deals mainly with characteristic functions representing subsets of memory pointers rather than the pointers themselves. This nonclassical symbolic paradigm is Turing universal, and, unlike the classical one, is efficiently implementable in homogeneous neural networks with temporal modulation topologically resembling that of the neocortex. : 29 pages, 7 figures |
format |
Report |
author |
Eliashberg, Victor |
author_facet |
Eliashberg, Victor |
author_sort |
Eliashberg, Victor |
title |
A nonclassical symbolic theory of working memory, mental computations, and mental set |
title_short |
A nonclassical symbolic theory of working memory, mental computations, and mental set |
title_full |
A nonclassical symbolic theory of working memory, mental computations, and mental set |
title_fullStr |
A nonclassical symbolic theory of working memory, mental computations, and mental set |
title_full_unstemmed |
A nonclassical symbolic theory of working memory, mental computations, and mental set |
title_sort |
nonclassical symbolic theory of working memory, mental computations, and mental set |
publisher |
arXiv |
publishDate |
2009 |
url |
https://dx.doi.org/10.48550/arxiv.0901.1152 https://arxiv.org/abs/0901.1152 |
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The Pointers |
genre_facet |
The Pointers |
op_rights |
arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
op_doi |
https://doi.org/10.48550/arxiv.0901.1152 |
_version_ |
1766216899675291648 |