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Emergence of Rules in Cell Assemblies of fLIF Neurons
Roman V. Belavkin, Christian R. Huyck
815 - 816
10.3233/978-1-58603-891-5-815
Frontiers in Artificial Intelligence and Applications
Volume 178: ECAI 2008
Abstract

Inspired by biological cognition, CABOT project explores the ways symbolic processing can emerge in a system of neural cell assemblies (CAs). Here we show how a stochastic meta–control process can regulate learning of associations between the CAs, the neural basis of symbols. An experiment illustrates the learning between CAs representing conditions actions pairs, which leads to CA–based representations of ‘if–then’ rules.

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