What is Minsky`s Critique of Perceptrons
The idea of Perceptrons came about after efforts to explain the mind
using computation were still going on. Perceptrons are a specific model
of the Neural Net theory, computers use symbol manipulation, while this
new theory uses interconnecting units which pass activity between
themselves.There are a number of inputs and one output, closely
replicating the manner in which the brain presents outputs. The form
that the output takes has a direct correlation to the combinations of
inputs and it was soon found that through Supervised Learning this node
system could learn. This means that by the process of trail and error,
a correct (incorrect) output strenghtens (weakens) the perceptron
connection. So if a response is the "right" one then the chances of
this output being chosen again are relatively higher.
However Minsky examined this carefully and noted that the system has no
difficulty in learning some outputs from certain inputs but others it
constantly gets wrong. The problem is greatly simplified if it is
stated that there are only two inputs, A and B. It will learn to choose
the correct output if A is a certain number(n), if B is a certain
number(n) or if this number(n) is A and B. In maths terms it can learn
the "AND" Rule and the "INCLUSIVE OR" Rule. Now if the system was asked
to come up with the correct answer if any one (as apposed to two) have
the the number(n) it seems to come to a standstill.It cannot learn the
correct response when one input is different from the other.The
mathematics student would call this the "EXCLUSIVE OR" Rule. This was
Minsky Critique of Perceptrons: the brain CAN do "EXCLUSIVE OR",
therefore this is a flawed theory.
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