Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results.

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Q. Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results.

(A) true – this works always, and these multiple perceptrons learn to classify even complex problems
(B) false – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do
(C) true – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded
(D) false – just having a single perceptron is enough

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✅ Correct Answer: (C) true – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded

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