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import numpy as np
from gradient_free_optimizers import RandomSearchOptimizer
def ackley_function(pos_new):
x = pos_new["x1"]
y = pos_new["x2"]
a1 = -20 * np.exp(-0.2 * np.sqrt(0.5 * (x * x + y * y)))
a2 = -np.exp(0.5 * (np.cos(2 * np.pi * x) + np.cos(2 * np.pi * y)))
score = a1 + a2 + 20
return -score
search_space = {
"x1": np.arange(-100, 101, 0.1),
"x2": np.arange(-100, 101, 0.1),
}
opt = RandomSearchOptimizer(search_space)
opt.search(ackley_function, n_iter=30000)
SimonBlanke /
Gradient-Free-Optimizers
