Schemas and Neurons: Two Levels of Neural Computing
For much of neural computing, the emphasis has been on tasks which can be solved by networks of simple units. In this paper I will argue that neural computing can learn from the study of the brain at many levels, and in particular will argue for schemas as appropriate functional units into which the solution of complex tasks may be decomposed. We may then exploit neural layers as structural units intermediate between structures subserving schemas and small neural circuits. The emphasis in this paper will be on Rana computatrix, modelling the frog as a biological robot, rather than on the use of schemas and neural networks in the design of brain-inspired devices. It is hoped that the broader implications will be clear to the reader.
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