From 8cb6b979bf3de749464dec9b8248380559a13364 Mon Sep 17 00:00:00 2001
From: Pascal Serrarens <pascal@passer.life>
Date: Wed, 12 Aug 2026 12:15:06 +0200
Subject: [PATCH] Add trivial mutation

---
 Runtime/Scripts/Core/Cluster.cs | 15 +++++++++++++++
 Runtime/Scripts/Core/Synapse.cs | 24 ++++++++++++++++++++++++
 2 files changed, 39 insertions(+)

diff --git a/Runtime/Scripts/Core/Cluster.cs b/Runtime/Scripts/Core/Cluster.cs
index d213186..75883a0 100644
--- a/Runtime/Scripts/Core/Cluster.cs
+++ b/Runtime/Scripts/Core/Cluster.cs
@@ -401,6 +401,21 @@ namespace NanoBrain {
             }
         }
 
+        public void GaussianAdditiveMutation(float sigma) {
+            foreach (Nucleus nucleus in this.nuclei) {
+                if (nucleus is Neuron neuron) {
+                    foreach (Synapse synapse in neuron.synapses) {
+                        if (synapse.trainable) {
+                            synapse.GaussianAdditiveMutation(sigma);
+                            //synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
+                            Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
+                        }
+                    }
+                }
+            }
+            
+        }
+
         #endregion Init
 
         #region Cluster Array
diff --git a/Runtime/Scripts/Core/Synapse.cs b/Runtime/Scripts/Core/Synapse.cs
index 481d663..d92af2f 100644
--- a/Runtime/Scripts/Core/Synapse.cs
+++ b/Runtime/Scripts/Core/Synapse.cs
@@ -110,6 +110,30 @@ namespace NanoBrain {
             // Check if the angle between the vectors is > 90 degrees
             return Vector3.Dot(a, b) < 0f;
         }
+
+        public void GaussianAdditiveMutation(float sigma) {
+            if (this.trainable == false)
+                return;
+
+            float deltaWeight = NormalDistribution.Sample(sigma);
+            this.weight += deltaWeight;
+        }
+    }
+
+    public static class NormalDistribution {
+        private static readonly System.Random rng = new();
+
+        // Returns a single sample from N(0, sigma^2)
+        public static float Sample(float sigma) {
+            // u1 must be > 0 to avoid log(0)
+            float u1 = 1.0f - (float)rng.NextDouble(); // in (0,1]
+            float u2 = (float) rng.NextDouble();       // in [0,1)
+
+            float stdNormal =
+                Mathf.Sqrt(-2.0f * Mathf.Log(u1)) * Mathf.Cos(2.0f * Mathf.PI * u2);
+
+            return sigma * stdNormal;
+        }
     }
 
     [Serializable]