AN AUTOMATON WITH BRAIN‐LIKE PROPERTIES

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Abstract
Starting with a Moore‐type automaton the bases for a brain‐like sequential machine are laid down. The problem is considered both at the level of a physical structure and a state structure. The logic is cellular and variable to accommodate learning and generalization. It is shown that this structure can “learn to live” in a consistent environment. Concepts such as recognition and recall of environmental events, short‐term memory, data generation (analogous to speech production) and attention are shown to be natural attributes of the model.

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