⟩ 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