In 1951 Marvin Minsky teamed with Dean Edmonds build the first artificial neural network that simulated a rat finding its way through a maze.
They designed the first (40 neuron) neurocomputer, SNARC (Stochastic Neural Analog Reinforcement Computer), with synapses that adjusted their weights (measures of synaptic permeabilities) according to the success of performing a specified task (Hebbian learning) The machine was built of tubes, motors, and clutches, and it successfully modeled the behavior of a rat in a maze searching for food.
As a student, Minsky had dreamed of producing machines which could learn by providing them with memory "neurones" connected to "synapses"; the machine would also have to possess past memory in order to function efficiently when faced with different situations.
In 1951 the "machine" was born, consisting of a labyrinth of valves, small motors, gears and wires linking up the various "neurones". Some of these wires were connected up at random to the various memory banks in order to achieve a degree of causality of events. The reason such a machine had been put together was to try and find the exit from a maze where the machine would play the part of a rat whose progress would be monitored on a light network.
When the system was completed it was possible to follow all the movements of the 'rat' within the maze and it was only through a design fault that it was found more than one 'rat' could be introduced which would then interact together. After various casual attempts the rats started 'thinking' on a logical basis helped along by reinforcement of correct choices made and the more advanced rats would then be followed by the ones left behind. This first practical example, built by Minsky with the help of Dean Edmonds, also included numerous casual connections between its various 'neurones', acting like a sort of nervous system able to overcome any eventual information interruption due to one of the neurones failing.