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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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