I am trying to use a simulated annealing algorithm to tune the weights of a neural network. I was going to use pybrain's
optimization.StochasticHillClimber class to implement simulated annealing, but I realize that Stochastic Hill Climbing and Simulated Annealing may be different algorithms.
From the code of the
StochasticHillClimber class, it looks like it does not decrease the Temperature
T variable each iteration. Is this the only difference between stochastic hill climbing and simulated annealing?