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Implementing Relational-Algebraic Operators for Improving Cognitive Abilities in Networks of Neural Cliques

Authors:
Ala Aboudib
Vincent Gripon
Baptiste Tessiau

Keywords: Cognitive modeling; artificial neural networks; relational algebra; associative memory; simulated annealing

Abstract:
Associative memories are devices capable of retrieving previously stored messages from parts of their content. They are used in a variety of applications including CPU caches, routers, intrusion detection systems, etc. They are also considered a good model for human memory, motivating the use of neural-based techniques. When it comes to cognition, it is important to provide such devices with the ability to perform complex requests, such as union, intersection, difference, projection and selection. In this paper, we extend a recently introduced associative memory model to perform relational algebra operations. We introduce new algorithms and discuss their performance which provides an insight on how the brain performs some high-level information processing tasks.

Pages: 36 to 41

Copyright: Copyright (c) IARIA, 2015

Publication date: March 22, 2015

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-390-2

Location: Nice, France

Dates: from March 22, 2015 to March 27, 2015