From Synapses to Rules - Discovering Symbolic Rules from Neural Processed Data (Hardcover, 2002 ed.)

One high-level ability of the human brain is to understand what it has learned. This seems to be the crucial advantage in comparison to the brain activity of other primates. At present we are technologically almost ready to artificially reproduce human brain tissue, but we still do not fully understand the information processing and the related biological mechanisms underlying this ability. Thus an electronic clone of the human brain is still far from being realizable. At the same time, around twenty years after the revival of the connectionist paradigm, we are not yet satisfied with the typical subsymbolic attitude of devices like neural networks: we can make them learn to solve even difficult problems, but without a clear explanation of why a solution works. Indeed, to widely use these devices in a reliable and non elementary way we need formal and understandable expressions of the learnt functions. of being tested, manipulated and composed with These must be susceptible other similar expressions to build more structured functions as a solution of complex problems via the usual deductive methods of the Artificial Intelligence. Many effort have been steered in this directions in the last years, constructing artificial hybrid systems where a cooperation between the sub symbolic processing of the neural networks merges in various modes with symbolic algorithms. In parallel, neurobiology research keeps on supplying more and more detailed explanations of the low-level phenomena responsible for mental processes.

General

Imprint:	Kluwer Academic / Plenum Publishers
Country of origin:	United States
Release date:	October 2002
First published:	October 2002
Editors:	Bruno Apolloni • Franz Kurfess
Dimensions:	254 x 178 x 32mm (L x W x T)
Format:	Hardcover
Pages:	388
Edition:	2002 ed.
ISBN-13:	978-0-306-47402-6
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	0-306-47402-6
Barcode:	9780306474026

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!