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authorMartijn van Beest <martijn.vanbeest@student.uva.nl>2017-10-19 08:56:12 +0200
committerMartijn van Beest <martijn.vanbeest@student.uva.nl>2017-10-19 08:56:12 +0200
commitd1d0c00ac9804a2daaab3d52a8b0578fefb08c5e (patch)
tree462e368246ebe549308da2b1fef2d8dd7c50970b
parent46ce50e38cabeaf173da2f41eb9b1e37f3587cbf (diff)
cleanup
-rw-r--r--Individual.java9
1 files changed, 4 insertions, 5 deletions
diff --git a/Individual.java b/Individual.java
index 8d82b62..a24297d 100644
--- a/Individual.java
+++ b/Individual.java
@@ -86,7 +86,6 @@ public class Individual
private void uncorrelatedMutationWithOneStepSize(double epsilon, Random rnd)
{
double tau = 0.9;
- //double epsilon = 0.025;
double gamma = tau * rnd.nextGaussian();
sigma[0] *= Math.exp(gamma);
sigma[0] = Math.max(sigma[0], epsilon);
@@ -100,7 +99,6 @@ public class Individual
{
double tau = Options.tau; // local learning rate (τ)
double tau2 = Options.tau2; // global learning rate (τ')
- //double epsilon = Options.epsilon;
double gamma = tau2 * rnd.nextGaussian();
@@ -114,14 +112,15 @@ public class Individual
private void correlatedMutation(double epsilon, Random rnd)
{
+ double tau = 0.05; // local learning rate
+ double tau2 = 0.9; // global learning rate
+
double beta = 5;
int n = value.length;
int sign;
int alpha_i;
int n_alpha = (int) n * (n - 1) / 2;
- double tau = 0.05; // local learning rate
- double tau2 = 0.9; // global learning rate
- //double epsilon = 0.001;
+
double[] means = new double[n];
double[] dx = new double[n];
double gamma = tau2 * rnd.nextGaussian();