Refactoring

.editorconfig

@@ -18,3 +18,6 @@ csharp_new_line_between_query_expression_clauses = true
 
 # Limit the number of characters in a line
 max_line_length = 100  # This setting does not enforce it; it's a guideline.
+
+[*.{cs,vb}]
+dotnet_diagnostic.IDE1006.severity = none

Assembly-CSharp.csproj

@@ -52,6 +52,7 @@
     <Compile Include="Assets/NanoBrain/NeuroidBehaviour.cs" />
     <Compile Include="Assets/NanoBrain/SensoryNeuroid.cs" />
     <Compile Include="Assets/Scenes/Boids/Scripts/SwarmControl.cs" />
+    <Compile Include="Assets/NanoBrain/Perception.cs" />
     <Compile Include="Assets/Scenes/Boids/Scripts/Boid.cs" />
     <Compile Include="Assets/NanoBrain/Neuroid.cs" />
   </ItemGroup>

Assets/NanoBrain/Editor/NeuroidWindow.cs

@@ -43,8 +43,9 @@ public class GraphEditorWindow : EditorWindow {
                 }
 
                 // If this neuroid is not visited while its output neuroid is visited
-                if (!neuronVisited.Contains(neuroid) && (neuroid.outputNeuroid == null ||
+                // Note: this does not yet work for multiple outputs yet (see the use of First())
-                    (neuronVisited.Contains(neuroid.outputNeuroid) && neuroid.outputNeuroid.layerIx == layerIx - 1))) {
+                if (!neuronVisited.Contains(neuroid) && (neuroid.outputNeuroids.Count == 0 ||
+                    (neuronVisited.Contains(neuroid.outputNeuroids.First()) && neuroid.outputNeuroids.First().layerIx == layerIx - 1))) {
                     // Add it to the next layer
                     currentLayer.neuroids.Add(neuroid);
                     neuroid.layerIx = layerIx;
@@ -54,7 +55,7 @@ public class GraphEditorWindow : EditorWindow {
                     Vector2Int neuroidPosition = new(layerIx, neuroidIx);
                     neuroidPositions[neuroid] = neuroidPosition;
                     neuroidIx++;
-                    Debug.Log($"Layer {layerIx} neuron {neuroidIx} id {neuroid.id} {neuroid.name}");
+                    Debug.Log($"Layer {layerIx} neuron {neuroidIx} name {neuroid.name}");
                 }
             }
 
@@ -110,9 +111,9 @@ public class GraphEditorWindow : EditorWindow {
             Vector3 parentPos = new(100 + layerNeuroidPos.x * 100, margin + layerNeuroidPos.y * spacing, 0.1f);
 
             int i = 0;
-            float inputSpacing = 200f / layerNeuroid.synapses.Count;
+            float inputSpacing = 200f / layerNeuroid.newSynapses.Count;
             float inputMargin = 100 + inputSpacing / 2;
-            foreach (Synapse synapse in layerNeuroid.synapses.Values) {
+            foreach (Synapse synapse in layerNeuroid.newSynapses.Values) {
                 if (synapse.neuroid != null) {
                     if (this.neuroidPositions.ContainsKey(synapse.neuroid)) {
 
@@ -144,7 +145,7 @@ public class GraphEditorWindow : EditorWindow {
         // Draw the tooltip
         GUIContent tooltip = new(
             $"{neuroid.name}" +
-            $"\nsynapse count {neuroid.synapses.Count}" +
+            $"\nsynapse count {neuroid.newSynapses.Count}" +
             $"\nValue: {neuroid.outputValue}" +
             $"\nStale: {neuroid.stale}");
             

Assets/NanoBrain/Neuroid.cs

@@ -29,17 +29,16 @@ public class NeuroidNetwork {
 }
 
 public class Neuroid {
-    public int id;
+    //public int id;
     public string name;
 
     public int layerIx;
     public int stale = 0;
 
-    public readonly Dictionary<int, Synapse> synapses = new();
+    public readonly Dictionary<Neuroid, Synapse> newSynapses = new();
 
     public Vector3 outputValue;
-    public Neuroid outputNeuroid;
+    public HashSet<Neuroid> outputNeuroids = new();
-    public int outputNeurix;
 
     public enum Mode {
         Sum,
@@ -52,69 +51,95 @@ public class Neuroid {
 
     public Neuroid(NeuroidNetwork net) {
         this.net = net;
+        if (this.net != null)
             this.net.neuroids.Add(this);
     }
 
-    public void SetOutputTo(Neuroid neuroid) {
+    public void AddSynapse(Neuroid input) {
-        this.outputNeuroid = neuroid;
+        input.AddReceiver(this);
-        // neuroid.inputNeuroids.Add(this);
+        this.newSynapses[input] = new(input, Vector3.zero, 1.0f);
-        this.outputNeurix = this.id;
+    }
+
+    public void AddReceiver(Neuroid receiver) {
+        this.outputNeuroids.Add(receiver);
     }
 
     public void ResetWeights() {
-        foreach (Synapse synapse in synapses.Values)
+        foreach (Synapse synapse in this.newSynapses.Values)
             synapse.weight = 1.0f;
     }
 
     public void SetWeight(Neuroid input, float weight) {
-        if (synapses.ContainsKey(input.id))
+        if (this.newSynapses.ContainsKey(input)) {
-            synapses[input.id] = new(input, synapses[input.id].value, weight);
+            this.newSynapses[input].weight = weight;
-        else
+        }
-            synapses[input.id] = new(input, Vector3.zero, weight);
+        else {
+            this.newSynapses[input] = new(input, Vector3.zero, weight);
+        }
     }
 
     public void GetInputFrom(Neuroid input, float weight = 1.0f) {
-        input.id = this.synapses.Count;
+        input.AddReceiver(this);
-        input.SetOutputTo(this);
+        this.newSynapses[input] = new(input, Vector3.zero, weight);
-        synapses[input.id] = new(input, Vector3.zero, weight);
     }
 
-    public void SetInput(int inputId, Vector3 value) {
+    public void SetInput(Neuroid input, Vector3 value) {
-        if (synapses.ContainsKey(inputId))
+        if (this.newSynapses.ContainsKey(input)) {
-            synapses[inputId].value = value;
+            Synapse synapse = this.newSynapses[input];
+            synapse.value = value;
+        }
         else
-            synapses[inputId] = new(null, value, 1.0f);
+            this.newSynapses[input] = new(null, value, 1.0f);
         UpdateState();
     }
-    public void SetInput(int inputIx, Vector3 value, float weight) {
+
-        if (synapses.ContainsKey(inputIx)) {
+    public void SetInput(Neuroid input, Vector3 value, float weight) {
-            Synapse synapse = synapses[inputIx];
+        if (this.newSynapses.ContainsKey(input)) {
+            Synapse synapse = this.newSynapses[input];
             synapse.value = value;
             synapse.weight = weight;
         }
         else
-            synapses[inputIx] = new(null, value, weight);
+            this.newSynapses[input] = new(null, value, weight);
         UpdateState();
     }
 
-    void UpdateState() {
+    public readonly Dictionary<int, Neuroid> fakeNeuroids = new();
+    public void SetInput(int thingId, Vector3 value, float weight, NeuroidNetwork net) {
+        if (fakeNeuroids.ContainsKey(thingId)) {
+            Neuroid fakeInput = fakeNeuroids[thingId];
+            Synapse synapse = this.newSynapses[fakeInput];
+            synapse.value = value;
+            synapse.weight = weight;
+        }
+        else {
+            fakeNeuroids[thingId] = new(net);
+            this.newSynapses[fakeNeuroids[thingId]] = new (null, value, weight);
+        }
+        UpdateState();
+    }
+
+
+    protected virtual void UpdateState() {
         Vector3 sum = Vector3.zero;
-        foreach (Synapse synapse in synapses.Values)
+        foreach (Synapse synapse in this.newSynapses.Values)
             sum += synapse.value * synapse.weight;
 
         this.outputValue = Activation(sum);
-        this.outputNeuroid?.SetInput(this.outputNeurix, this.outputValue);
+        foreach (Neuroid neuroid in outputNeuroids) {
+            neuroid?.SetInput(this, this.outputValue);
+        }
         this.stale = 0;
     }
 
     Vector3 Activation(Vector3 sum) {
-        if (synapses.Count == 0 && mode == Mode.Average)
+        if (this.newSynapses.Count == 0 && mode == Mode.Average)
-            Debug.LogWarning($"{this.id} {this.name} has zero synapses for average");
+            Debug.LogWarning($"{this.name} has zero synapses for average");
         if (float.IsNaN(sum.magnitude))
-            Debug.LogWarning($"{this.id} {this.name} sum is nan");
+            Debug.LogWarning($"{this.name} sum is nan");
         return mode switch {
             Mode.Sum => sum,
-            Mode.Average => sum / synapses.Count,
+            Mode.Average => sum / this.newSynapses.Count,
             _ => sum,
         };
         //return sum;  //(sum.magnitude > 0.5f) ? sum : Vector3.zero;

Assets/NanoBrain/Perception.cs

@@ -0,0 +1,83 @@
+using System.Collections.Generic;
+using UnityEngine;
+
+public class Perception {
+    public SensoryNeuroid[] sensoryNeuroids = new SensoryNeuroid[7];
+    //public Neuroid[] velocitySensors = new Neuroid[7];
+    public NeuroidNetwork neuroidNet { get; protected set; }
+
+    public HashSet<Neuroid> receivers { get; protected set; }
+
+    public Perception(NeuroidNetwork neuroidNet) {
+        this.neuroidNet = neuroidNet;
+        this.receivers = new();
+    }
+
+    // public void SendOutputTo(Neuroid receiver) {
+    //     foreach (SensoryNeuroid neuroid in sensoryNeuroids) {
+    //         if (neuroid != null) {
+    //             neuroid.AddReceiver(receiver);
+    //             receiver.newSynapses[neuroid] = new (neuroid, Vector3.zero, 1.0f);
+    //         }
+    //     }
+    // }
+
+    public void SendPositions(Neuroid receiver) {
+        receivers.Add(receiver);
+        foreach (SensoryNeuroid neuroid in sensoryNeuroids) {
+            if (neuroid != null) {
+                neuroid.AddReceiver(receiver);
+                receiver.newSynapses[neuroid] = new (neuroid, Vector3.zero, 1.0f);
+            }
+        }
+    }
+    public void SendVelocities(Neuroid receiver) {
+        receivers.Add(receiver);
+        foreach (SensoryNeuroid neuroid in sensoryNeuroids) {
+            if (neuroid != null && neuroid.velocityNeuroid != null) {
+                neuroid.velocityNeuroid.AddReceiver(receiver);
+                receiver.newSynapses[neuroid] = new (neuroid, Vector3.zero, 1.0f);
+            }
+        }
+    }
+
+    public void ProcessStimulus(int thingId, Vector3 localPosition) {
+        int availableIx = -1;
+        SensoryNeuroid leastInterestingNeuroid = null;
+        for (int i = 0; i < sensoryNeuroids.Length; i++) {
+            if (sensoryNeuroids[i] == null || sensoryNeuroids[i].IsStale())
+                availableIx = i;
+            else if (sensoryNeuroids[i].receptor.thingId == thingId) {
+                sensoryNeuroids[i].receptor.position = localPosition;
+                return;
+            }
+            if (sensoryNeuroids[i] != null) {
+                if (leastInterestingNeuroid == null || leastInterestingNeuroid.receptor.position.magnitude > sensoryNeuroids[i].receptor.position.magnitude)
+                    leastInterestingNeuroid = sensoryNeuroids[i];
+            }
+        }
+        if (availableIx != -1) {
+            if (sensoryNeuroids[availableIx] != null) {
+                // Debug.Log($"revived receptor {availableIx} for {thingId}");
+                sensoryNeuroids[availableIx].receptor.thingId = thingId;
+                sensoryNeuroids[availableIx].receptor.position = localPosition;
+            }
+            else {
+                // Debug.Log($"new receptor for {thingId}");
+                SensoryNeuroid neuroid = new(neuroidNet, thingId);
+                foreach (Neuroid receiver in receivers)
+                    receiver.GetInputFrom(neuroid);
+
+                sensoryNeuroids[availableIx] = neuroid;
+                neuroid.receptor.position = localPosition;
+            }
+        }
+        else if (leastInterestingNeuroid != null) {
+            //Debug.Log($"replaced receptor {leastInterestingNeuroid.thingId} for {thingId}");
+            leastInterestingNeuroid.receptor.thingId = thingId;
+            leastInterestingNeuroid.receptor.position = localPosition;
+        }
+
+        //Debug.LogWarning($"No available receptor for {id}");
+    }
+}

Assets/NanoBrain/Perception.cs.meta

@@ -0,0 +1,2 @@
+fileFormatVersion: 2
+guid: 37d94d399d30e6eb996236adabad87ee

Assets/NanoBrain/SensoryNeuroid.cs

@@ -1,32 +1,70 @@
+using System.Linq;
 using UnityEngine;
 
+public class SensoryNeuroid : Neuroid {
+    // A neuroid which has no neurons as input
+    // But receives value from a receptor
+    public Receptor receptor;
+    public VelocityNeuroid velocityNeuroid;
+
+    public SensoryNeuroid(NeuroidNetwork net, int thingId) : base(net) {
+        this.name = "sensory neuroid";
+        this.receptor = new Receptor {
+            neuroid = this,
+            thingId = thingId
+        };
+        this.velocityNeuroid = new(net);
+        // The velocity neuroid received position data from this
+        this.AddReceiver(velocityNeuroid);
+    }
+
+}
+
 public class Receptor {
+
     public SensoryNeuroid neuroid;
-    public void SetValue(Vector3 value) {
+
-        if (neuroid != null) {
+    public int thingId;
-            neuroid.SetInput(neuroid.id, value);
+    /// <summary>
-        }
+    /// Local position of the thing
-    }
+    /// </summary>
-    public Vector3 GetValue() {
+    public virtual Vector3 position {
+        get {
             if (neuroid != null)
-            return neuroid.synapses[neuroid.id].value;
+                return neuroid.newSynapses[neuroid].value;
             else
                 return Vector3.zero;
         }
+        set {
+            if (neuroid != null)
+                neuroid.SetInput(neuroid, value);
+        }
+    }
 }
 
+public class VelocityNeuroid : Neuroid {
+    // Would be best if this was received through a synapse via a loop....
+    private Vector3 lastPosition = Vector3.zero;
+    private float lastValueTime = 0;
 
-public class SensoryNeuroid : Neuroid {
+    public VelocityNeuroid(NeuroidNetwork net) : base(net) {
-    public Receptor receptor;
-    public int thingId;
-
-    public SensoryNeuroid(NeuroidNetwork net, int id) : base(net) {
-        this.name = "sensory neuroid";
-        // this.id = id;
-        this.thingId = id;
-        this.receptor = new Receptor {
-            neuroid = this
-        };
     }
 
+    protected override void UpdateState() {
+        // Assuming only one synapse for now....
+        Vector3 currentPosition = this.newSynapses.First().Value.value;
+        float currentValueTime = Time.time;
+
+        float deltaTime = currentValueTime - lastValueTime;
+        Vector3 translation = currentPosition - lastPosition;
+        Vector3 velocity = translation / deltaTime;
+
+        // No activation function...
+        this.outputValue = velocity;
+        foreach (Neuroid receiver in outputNeuroids)
+            receiver?.SetInput(this, this.outputValue);
+        this.stale = 0;
+
+        this.lastValueTime = Time.time;
+    }
 }

Assets/Scenes/Boids/Boids.unity

@@ -378,7 +378,7 @@ MonoBehaviour:
   separationForce: 5
   separationDistance: 0.3
   bodyForce: 20
-  perceptionDistance: 2
+  perceptionDistance: 1
   boundaryForce: 5
   spaceSize: {x: 10, y: 10, z: 10}
   boundaryWidth: {x: 1, y: 1, z: 1}
@@ -394,7 +394,7 @@ MonoBehaviour:
   m_Script: {fileID: 11500000, guid: ec888ca5333d45a438f9f417fa5ce135, type: 3}
   m_Name: 
   m_EditorClassIdentifier: Assembly-CSharp::SwarmSpawn
-  count: 1000
+  count: 5
   boidPrefab: {fileID: 8702527964058765413, guid: f9c706268554ce449a8773675b2864b8, type: 3}
   spawnAreaSize: {x: 0.5, y: 0.5, z: 0.5}
   minDelay: 0.05

Assets/Scenes/Boids/Scripts/Boid.cs

@@ -19,7 +19,8 @@ public class Boid : MonoBehaviour {
 
     readonly Collider[] results = new Collider[10];
 
-    public SensoryNeuroid[] neighbourSensor = new SensoryNeuroid[6];
+    //public SensoryNeuroid[] neighbourSensor = new SensoryNeuroid[6];
+    public Perception perception;
 
     public NeuroidNetwork neuroidNet = new();
     public Neuroid bodyVector;
@@ -40,11 +41,14 @@ public class Boid : MonoBehaviour {
 
         bounds = new(sc.transform.position, sc.spaceSize - 2 * sc.boundaryWidth);
 
+        perception = new Perception(neuroidNet);
         //neighbourSensor = new(neuroidNet) { name = "Neighbour", id = 879 };
 
         cohesion = new(neuroidNet) { name = "Cohesion", mode = Neuroid.Mode.Sum };
+        perception.SendPositions(cohesion);
         //cohesion.GetInputFrom(neighbourSensor);
         alignment = new(neuroidNet) { name = "Alignment", mode = Neuroid.Mode.Average };
+        //perception.SendVelocities(alignment);
         separation = new(neuroidNet) { name = "Separation", mode = Neuroid.Mode.Sum };
         target = new(neuroidNet) { name = "Target", mode = Neuroid.Mode.Sum };
         boundary = new(neuroidNet) { name = "Boundary", mode = Neuroid.Mode.Sum };
@@ -78,15 +82,15 @@ public class Boid : MonoBehaviour {
                 Vector3 localPosition = neighbour.transform.position - this.transform.position;
                 Vector3 relativeVelocity = neighbour.velocity - this.velocity;
 
-                int id = neighbour.GetInstanceID();
+                int thingId = neighbour.GetInstanceID();
-                ProcessStimulus(id, localPosition);
+                perception.ProcessStimulus(thingId, localPosition);
 
                 Vector3 separationForce = -localPosition / localPosition.sqrMagnitude;
                 // which is equivalent to -(localPosition.normalized / localPosition.magnitude)
 
-                separation.SetInput(id, separationForce, sc.separationDistance);
+                separation.SetInput(thingId, separationForce, sc.separationDistance, neuroidNet);
-                //cohesion.SetInput(id, localPosition, sc.cohesionForce);
+                //cohesion.SetInput(thingId, localPosition, sc.cohesionForce);
-                alignment.SetInput(id, relativeVelocity, sc.alignmentForce);
+                alignment.SetInput(thingId, relativeVelocity, sc.alignmentForce, neuroidNet);
                 neighbourCount++;
 
             }
@@ -108,7 +112,7 @@ public class Boid : MonoBehaviour {
             Vector3 direction = (sc.transform.position - this.transform.position).normalized;
             outside = direction * magnitude;
 
-            boundary.SetInput(id, outside, sc.boundaryForce);
+            boundary.SetInput(id, outside, sc.boundaryForce, neuroidNet);
             // Debug.Log($"boundary {this.transform.position} {outside} force = {outside * sc.boundaryForce}");
         }
 
@@ -128,7 +132,7 @@ public class Boid : MonoBehaviour {
         //Debug.Log($"neighbours: {neighbourCount} synapses: {cohesion.synapses.Count}");
         neuroidNet.Update();
     }
-
+/*
     Receptor GetReceptor(Neuroid perceptionNeuroid, int id) {
         int availableIx = -1;
         for (int i = 0; i < neighbourSensor.Length; i++) {
@@ -157,7 +161,7 @@ public class Boid : MonoBehaviour {
     }
 
 
-
+/*
     void ProcessStimulus(int thingId, Vector3 value) {
         int availableIx = -1;
         SensoryNeuroid leastInterestingNeuroid = null;
@@ -168,8 +172,6 @@ public class Boid : MonoBehaviour {
                 neighbourSensor[i].receptor.SetValue(value);
                 return;
             }
-            // if (leastInterestingIx == -1 || neighbourSensor[leastInterestingIx].receptor.GetValue().magnitude > neighbourSensor[i].receptor.GetValue().magnitude)
-            //     leastInterestingIx = i;
             if (neighbourSensor[i] != null) {
                 if (leastInterestingNeuroid == null || leastInterestingNeuroid.receptor.GetValue().magnitude > neighbourSensor[i].receptor.GetValue().magnitude)
                     leastInterestingNeuroid = neighbourSensor[i];
@@ -197,7 +199,7 @@ public class Boid : MonoBehaviour {
 
         //Debug.LogWarning($"No available receptor for {id}");
     }
-
+*/
     void OnDrawGizmosSelected() {
         Gizmos.DrawWireSphere(transform.position, sc.perceptionDistance);
     }