We will look at both a genetic algorithm technique and a simulated annealing technique. Decide the parameter set. Have a way to evaluate the parameter set.
Evaluation is definitely well-behaved.
All nodes in a separate zone. Node 0.0 will control the search. If a candidate turns out to be better than some member of the current population, then we replace the worst member of the current population with the new individual. We represent the set of parameters that define an individual as a string of bits. Go through each bit of the bit string, and mutate it with some small probability.