I have been wrestling with this spiked neural network problem for a few
days. Im trying to think how one could create a spiked neural network
(because it is the most biologically realistic) that automatically
finds the structure to learn the XOR function.
For example if this was the OR function, we would have two neurons for
the inputs and one for the output, and hebbian learning would work just
fine for correlating the inputs with the output. However for the XOR
function we have somehow got to find a way of automatically creating a
neuron that will fire when both inputs are on, and have a negative
weight to the output.
Does anyone know if there is any algorithm for automatically finding
the structure? Hebbian style STDP (Spike timing dependant plasticity)
is great for correlating existing neurons, but there has to be some way
of automatically creating new neurons when the structure requires it.