I'm programming a neural network. I know that I should initialize the network by picking random weights. How do I pick a random weight for the connections to bias nodes? What distribution should I use for these weights? I can pick a random value from the range $[0,U]$, but what value should I use for the upper limit $U$?
What I've tried: I've set $U$ to correspond to the number of inputs to a neuron. Then the percentage of inputs '$K$' that the node needs to fire (this is set in the agents genome) which is set from 0.0 to 1.0, is multiplied with $U$ to get the weight of the bias node. So a node with a $K$ value of 0.7 and 40 inputs would have a bias weight of $U * K = 0.7*40 = 28$. Am I correct for assuming that $U$ would be the total number of a nodes inputs? Or am I approaching this wrong?