NanoBrain/NanoBrain-unitypackage
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Simplified synapses, NanoBrain component

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This commit is contained in:
Pascal Serrarens 2025-12-03 10:16:36 +01:00
parent 9a6ae0e071
commit 145e033d4c
15 changed files with 364 additions and 112 deletions
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1
Assembly-CSharp-Editor.csproj
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@ -48,6 +48,7 @@
<Analyzer Include="/home/pascal/Unity/Hub/Editor/6000.2.13f1/Editor/Data/Tools/Unity.SourceGenerators/Unity.UIToolkit.SourceGenerator.dll" />
</ItemGroup>
<ItemGroup>
<Compile Include="Assets/NanoBrain/Editor/NanoBrain_Editor.cs" />
<Compile Include="Assets/NanoBrain/Editor/NeuroidWindow.cs" />
</ItemGroup>
<ItemGroup>

1
Assembly-CSharp.csproj
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@ -50,6 +50,7 @@
<ItemGroup>
<Compile Include="Assets/Scenes/Boids/Scripts/SwarmSpawner.cs" />
<Compile Include="Assets/NanoBrain/NeuroidBehaviour.cs" />
<Compile Include="Assets/NanoBrain/NanoBrain.cs" />
<Compile Include="Assets/NanoBrain/SensoryNeuroid.cs" />
<Compile Include="Assets/Scenes/Boids/Scripts/SwarmControl.cs" />
<Compile Include="Assets/Scenes/Boids/Scripts/RoamingNucleus.cs" />

203
Assets/NanoBrain/Editor/NanoBrain_Editor.cs Normal file
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@ -0,0 +1,203 @@
using System.Collections.Generic;
using UnityEngine;
using UnityEditor;
[CustomEditor(typeof(NanoBrain))]
public class NanoBrain_Editor : Editor {
private Nucleus currentNucleus;
private List<NeuroidLayer> layers = new();
private Dictionary<Nucleus, Vector2Int> neuroidPositions = new();
#region Start
private void OnEnable() {
SelectNeuron();
}
private void SelectNeuron() {
GameObject selectedObject = ((NanoBrain)target).gameObject;
if (!selectedObject.TryGetComponent(out Boid boid))
return;
Neuroid neuroid = boid.totalForce;
this.currentNucleus = neuroid;
BuildLayers();
Debug.Log($"Layercount = {this.layers.Count}");
}
#endregion Start
#region Update
public override void OnInspectorGUI() {
DrawGraph();
DrawDefaultInspector();
}
private void BuildLayers() {
// A temporary list to track what's been added to layers
this.layers = new();
int layerIx = 0;
Nucleus selectedNucleus = this.currentNucleus;
if (selectedNucleus == null)
return;
NeuroidLayer currentLayer = new() { ix = layerIx };
foreach (Neuroid outputNeuroid in selectedNucleus.outputNeuroids) {
if (outputNeuroid != null) {
AddToLayer(currentLayer, outputNeuroid);
Debug.Log($"layer {layerIx} nucleus {outputNeuroid.name}");
}
}
if (currentLayer.neuroids.Count > 0) {
this.layers.Add(currentLayer);
layerIx++;
currentLayer = new() { ix = layerIx };
}
AddToLayer(currentLayer, selectedNucleus);
this.layers.Add(currentLayer);
Debug.Log($"layer {layerIx} nucleus {selectedNucleus.name}");
layerIx++;
currentLayer = new() { ix = layerIx };
foreach (Nucleus input in selectedNucleus.synapses.Keys) {
AddToLayer(currentLayer, input);
Debug.Log($"layer {layerIx} nucleus {input.name}");
}
if (currentLayer.neuroids.Count > 0) {
this.layers.Add(currentLayer);
}
}
private void AddToLayer(NeuroidLayer layer, Nucleus nucleus) {
layer.neuroids.Add(nucleus);
nucleus.layerIx = layer.ix;
// Store its position
Vector2Int neuroidPosition = new(layer.ix, layer.neuroids.Count - 1);
neuroidPositions[nucleus] = neuroidPosition;
}
private void DrawGraph() {
if (currentNucleus == null)
return;
Rect outer = EditorGUILayout.GetControlRect(false, 400);
GUI.BeginGroup(outer);
foreach (NeuroidLayer layer in layers)
DrawLayer(layer);
GUI.EndGroup();
}
private void DrawLayer(NeuroidLayer layer) {
int nodeCount = layer.neuroids.Count;
float maxValue = 0;
foreach (Nucleus nucleus in layer.neuroids) {
if (nucleus is Neuroid neuroid) {
float value = neuroid.outputValue.magnitude;
if (value > maxValue)
maxValue = value;
}
}
float spacing = 400f / nodeCount;
float margin = 10 + spacing / 2;
foreach (Nucleus layerNucleus in layer.neuroids) {
if (layerNucleus is Neuroid layerNeuroid) {
Vector2Int layerNeuroidPos = this.neuroidPositions[layerNeuroid];
Vector3 parentPos = new(100 + layerNeuroidPos.x * 100, margin + layerNeuroidPos.y * spacing, 0.1f);
int i = 0;
float inputSpacing = 400f / layerNeuroid.synapses.Count;
float inputMargin = 10 + inputSpacing / 2;
// foreach (Synapse synapse in layerNeuroid.synapses.Values) {
// if (synapse.neuroid != null) {
// if (this.neuroidPositions.ContainsKey(synapse.neuroid)) {
// Vector2Int inputNeuroidPos = this.neuroidPositions[synapse.neuroid];
foreach ((Nucleus neuroid, Synapse synapse) in layerNeuroid.synapses) {
if (neuroid != null) {
if (this.neuroidPositions.ContainsKey(neuroid)) {
Vector2Int inputNeuroidPos = this.neuroidPositions[neuroid];
if (inputNeuroidPos.x == layerNeuroidPos.x + 1) {
Vector3 pos = new(100 + inputNeuroidPos.x * 100, inputMargin + inputNeuroidPos.y * inputSpacing, 0.0f);
float brightness = synapse.weight / 10.0f;
Handles.color = new Color(brightness, brightness, brightness);
Handles.DrawLine(parentPos, pos);
}
}
}
}
float size = 20;
if (layerNeuroid.IsStale())
Handles.color = Color.black;
else {
float brightness = layerNeuroid.outputValue.magnitude / maxValue;
Handles.color = new Color(brightness, brightness, brightness);
}
Handles.DrawSolidDisc(parentPos, Vector3.forward, size);
Vector3 labelPos = parentPos - Vector3.down * (size + 0.2f); // below disc along up axis
GUIStyle style = new GUIStyle(EditorStyles.label) {
alignment = TextAnchor.UpperCenter,
normal = { textColor = Color.white },
fontStyle = FontStyle.Bold
};
Handles.Label(labelPos, layerNeuroid.name, style);
Rect neuronRect = new(parentPos.x - size, parentPos.y - size, size * 2, size * 2);
int id = GUIUtility.GetControlID(FocusType.Passive);
Event e = Event.current;
EventType et = e.GetTypeForControl(id);
if (e != null && neuronRect.Contains(e.mousePosition)) {
HandleMouseHover(layerNeuroid, neuronRect);
// Process click
Debug.Log($"{et}");
if (et == EventType.MouseDown && e.button == 0) {
// Consume the event so the scene doesn't also handle it
e.Use();
HandleDiscClicked(layerNeuroid);
}
}
i++;
}
}
}
private void HandleMouseHover(Neuroid neuroid, Rect rect) {
GUIContent tooltip;
if (neuroid is SensoryNeuroid sensoryNeuroid) {
tooltip = new(
$"{sensoryNeuroid.name}" +
$"\nThing {sensoryNeuroid.receptor.thingId}" +
$"\nValue: {neuroid.outputValue}" +
$"\nStale: {neuroid.stale}");
}
else {
tooltip = new(
$"{neuroid.name}" +
$"\nsynapse count {neuroid.synapses.Count}" +
$"\nValue: {neuroid.outputValue}" +
$"\nStale: {neuroid.stale}");
}
Vector2 mousePosition = Event.current.mousePosition;
// Display tooltip with some offset
Vector2 tooltipSize = GUI.skin.box.CalcSize(tooltip);
Rect tooltipRect = new Rect(mousePosition.x + 10, mousePosition.y + 10, tooltipSize.x, tooltipSize.y);
GUI.Box(tooltipRect, tooltip);
}
private void HandleDiscClicked(Nucleus nucleus) {
this.currentNucleus = nucleus;
BuildLayers();
}
#endregion Update
}

2
Assets/NanoBrain/Editor/NanoBrain_Editor.cs.meta Normal file
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@ -0,0 +1,2 @@
fileFormatVersion: 2
guid: 2299b68d073cc5c31915f591deb79ddc

21
Assets/NanoBrain/Editor/NeuroidWindow.cs
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@ -36,6 +36,8 @@ public class GraphEditorWindow : EditorWindow {
int layerIx = 0;
Nucleus selectedNucleus = this.currentNucleus;
if (selectedNucleus == null)
return;
NeuroidLayer currentLayer = new() { ix = layerIx };
foreach (Neuroid outputNeuroid in selectedNucleus.outputNeuroids) {
@ -58,9 +60,10 @@ public class GraphEditorWindow : EditorWindow {
currentLayer = new() { ix = layerIx };
int six = 0;
foreach (Synapse synapse in selectedNucleus.synapses.Values) {
Debug.Log($"Synapse {six}");
Nucleus input = synapse.neuroid;
// foreach (Synapse synapse in selectedNucleus.synapses.Values) {
// Debug.Log($"Synapse {six}");
// Nucleus input = synapse.neuroid;
foreach ((Nucleus input, Synapse synapse) in selectedNucleus.synapses) {
if (input != null) {
AddToLayer(currentLayer, input);
Debug.Log($"layer {layerIx} nucleus {input.name}");
@ -172,11 +175,15 @@ public class GraphEditorWindow : EditorWindow {
int i = 0;
float inputSpacing = 400f / layerNeuroid.synapses.Count;
float inputMargin = 100 + inputSpacing / 2;
foreach (Synapse synapse in layerNeuroid.synapses.Values) {
if (synapse.neuroid != null) {
if (this.neuroidPositions.ContainsKey(synapse.neuroid)) {
// foreach (Synapse synapse in layerNeuroid.synapses.Values) {
// if (synapse.neuroid != null) {
// if (this.neuroidPositions.ContainsKey(synapse.neuroid)) {
Vector2Int inputNeuroidPos = this.neuroidPositions[synapse.neuroid];
// Vector2Int inputNeuroidPos = this.neuroidPositions[synapse.neuroid];
foreach ((Nucleus neuroid, Synapse synapse) in layerNeuroid.synapses) {
if (neuroid != null) {
if (this.neuroidPositions.ContainsKey(neuroid)) {
Vector2Int inputNeuroidPos = this.neuroidPositions[neuroid];
if (inputNeuroidPos.x == layerNeuroidPos.x + 1) {
Vector3 pos = new(100 + inputNeuroidPos.x * 100, inputMargin + inputNeuroidPos.y * inputSpacing, 0.0f);

19
Assets/NanoBrain/NanoBrain.cs Normal file
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@ -0,0 +1,19 @@
using System.Collections.Generic;
using UnityEngine;
public class NanoBrain : MonoBehaviour {
public List<Neuroid> neuroids = new();
public Neuroid AddNeuron(string name) {
Neuroid neuroid = new(this, name);
return neuroid;
}
public void Update() {
foreach (Neuroid neuroid in neuroids) {
neuroid.stale++;
if (neuroid.IsStale())
neuroid.outputValue = Vector3.zero;
}
}
}

2
Assets/NanoBrain/NanoBrain.cs.meta Normal file
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@ -0,0 +1,2 @@
fileFormatVersion: 2
guid: 74e1478743ac3bc078cbe8501c287e98

103
Assets/NanoBrain/Neuroid.cs
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@ -3,32 +3,30 @@ using UnityEngine;
using System.Linq;
public class Synapse {
public Synapse(Nucleus neuroid, Vector3 value, float weight) {
this.neuroid = neuroid;
this.value = value;
public Synapse(Nucleus neuroid, float weight = 1.0f) {
//this.neuroid = neuroid;
this.weight = weight;
}
public Nucleus neuroid;
public Vector3 value;
//public Nucleus neuroid;
public float weight;
}
public class NeuroidNetwork {
public List<Neuroid> neuroids = new();
// public class NeuroidNetwork {
// public List<Neuroid> neuroids = new();
public Neuroid AddNeuron(string name) {
Neuroid neuroid = new(this, name);
return neuroid;
}
// public Neuroid AddNeuron(string name) {
// Neuroid neuroid = new(this, name);
// return neuroid;
// }
public void Update() {
foreach (Neuroid neuroid in neuroids) {
neuroid.stale++;
if (neuroid.IsStale())
neuroid.outputValue = Vector3.zero;
}
}
}
// public void Update() {
// foreach (Neuroid neuroid in neuroids) {
// neuroid.stale++;
// if (neuroid.IsStale())
// neuroid.outputValue = Vector3.zero;
// }
// }
// }
public class Neuroid : Nucleus {
public int stale = 0;
@ -40,19 +38,21 @@ public class Neuroid : Nucleus {
public bool inverse = false;
public float exponent = 1.0f;
public NeuroidNetwork net;
//public NeuroidNetwork net;
public NanoBrain net;
public Neuroid(NeuroidNetwork net, string name) : base(name) {
// public Neuroid(NeuroidNetwork net, string name) : base(name) {
public Neuroid(NanoBrain net, string name) : base(name) {
this.net = net;
if (this.net != null)
this.net.neuroids.Add(this);
else
else
Debug.LogError("No neuroid network");
}
public void AddSynapse(Neuroid input) {
input.AddReceiver(this);
this.synapses[input] = new(input, Vector3.zero, 1.0f);
this.synapses[input] = new(input);
}
// public void AddReceiver(Neuroid receiver) {
@ -69,33 +69,28 @@ public class Neuroid : Nucleus {
this.synapses[input].weight = weight;
}
else {
this.synapses[input] = new(input, Vector3.zero, weight);
this.synapses[input] = new(input, weight);
}
}
public void GetInputFrom(Neuroid input, float weight = 1.0f) {
input.AddReceiver(this);
this.synapses[input] = new(input, Vector3.zero, weight);
this.synapses[input] = new(input, weight);
}
public void SetInput(Neuroid input, Vector3 value) {
if (this.synapses.ContainsKey(input)) {
Synapse synapse = this.synapses[input];
synapse.value = value;
}
else
this.synapses[input] = new(null, value, 1.0f);
public void SetInput(Neuroid input) {
if (this.synapses.ContainsKey(input) == false)
this.synapses[input] = new(input);
UpdateState();
}
public void SetInput(Neuroid input, Vector3 value, float weight) {
public void SetInput(Neuroid input, float weight) {
if (this.synapses.ContainsKey(input)) {
Synapse synapse = this.synapses[input];
synapse.value = value;
synapse.weight = weight;
}
else
this.synapses[input] = new(null, value, weight);
this.synapses[input] = new(input, weight);
UpdateState();
}
@ -105,38 +100,28 @@ public class Neuroid : Nucleus {
// In case this was the last synapse, we reset the output because in this case no updates from synapses will follow.
this.outputValue = Vector3.zero;
foreach (Neuroid neuroid in this.outputNeuroids)
neuroid.SetInput(this, this.outputValue);
neuroid.SetInput(this);
}
}
// 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.synapses[fakeInput];
// synapse.value = value;
// synapse.weight = weight;
// }
// else {
// fakeNeuroids[thingId] = new(net);
// this.synapses[fakeNeuroids[thingId]] = new(null, value, weight);
// }
// UpdateState();
// }
protected virtual void UpdateState() {
public virtual void UpdateState() {
Vector3 result = Vector3.zero;
foreach (Synapse synapse in this.synapses.Values) {
// if (synapse.neuroid == null)
// continue;
Vector3 direction = synapse.value.normalized;
float magnitude = synapse.value.magnitude;
foreach ((Nucleus nucleus, Synapse synapse) in this.synapses) {
// foreach (Synapse synapse in this.synapses.Values) {
// if (synapse.neuroid == null)
// Debug.LogWarning(" disconnected synapse");
// if (synapse.value != synapse.neuroid.outputValue)
// Debug.LogWarning("synapse value error");
// Vector3 direction = synapse.value.normalized;
// float magnitude = synapse.value.magnitude;
// Vector3 direction = synapse.neuroid.outputValue.normalized;
// float magnitude = synapse.neuroid.outputValue.magnitude;
Vector3 direction = nucleus.outputValue.normalized;
float magnitude = nucleus.outputValue.magnitude;
magnitude = synapse.weight * Mathf.Pow(magnitude, exponent);
if (inverse)
if (inverse && magnitude > 0)
magnitude = 1 / magnitude;
result += direction * magnitude;
}
@ -145,7 +130,7 @@ public class Neuroid : Nucleus {
this.outputValue = result;
foreach (Neuroid neuroid in this.outputNeuroids)
neuroid.SetInput(this, this.outputValue);
neuroid.SetInput(this);
this.stale = 0;
}

2
Assets/NanoBrain/Nucleus.cs
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@ -16,6 +16,6 @@ public class Nucleus {
public virtual void AddReceiver(Neuroid receiver) {
this.outputNeuroids.Add(receiver);
receiver.synapses[this] = new(this, Vector3.zero, 1.0f);
receiver.synapses[this] = new(this);
}
}

10
Assets/NanoBrain/Perception.cs
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@ -5,7 +5,8 @@ using UnityEngine;
public class Perception : Nucleus {
public SensoryNeuroid[] sensoryNeuroids = new SensoryNeuroid[7];
public NeuroidNetwork neuroidNet { get; protected set; }
// public NeuroidNetwork neuroidNet { get; protected set; }
public NanoBrain neuroidNet { get; protected set; }
public class Receiver {
public int thingType = 0;
@ -15,7 +16,8 @@ public class Perception : Nucleus {
public HashSet<Receiver> positionReceivers { get; protected set; }
public HashSet<Receiver> velocityReceivers { get; protected set; }
public Perception(NeuroidNetwork neuroidNet) : base("Perception") {
// public Perception(NeuroidNetwork neuroidNet) : base("Perception") {
public Perception(NanoBrain neuroidNet) : base("Perception") {
this.neuroidNet = neuroidNet;
this.positionReceivers = new();
this.velocityReceivers = new();
@ -30,7 +32,7 @@ public class Perception : Nucleus {
foreach (SensoryNeuroid neuroid in sensoryNeuroids) {
if (neuroid != null) {
neuroid.AddReceiver(receivingNeuroid);
receivingNeuroid.synapses[neuroid] = new(neuroid, Vector3.zero, weight);
receivingNeuroid.synapses[neuroid] = new(neuroid, weight);
}
}
}
@ -43,7 +45,7 @@ public class Perception : Nucleus {
foreach (SensoryNeuroid neuroid in sensoryNeuroids) {
if (neuroid != null && neuroid.velocityNeuroid != null) {
neuroid.velocityNeuroid.AddReceiver(receivingNeuroid);
receivingNeuroid.synapses[neuroid] = new(neuroid, Vector3.zero, 1.0f);
receivingNeuroid.synapses[neuroid] = new(neuroid);
}
}
}

80
Assets/NanoBrain/SensoryNeuroid.cs
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@ -1,13 +1,36 @@
using System.Collections.Generic;
using System.Linq;
using UnityEngine;
public class Receptor {
public SensoryNeuroid neuroid;
public int thingId;
public Vector3 value;
/// <summary>
/// Local position of the thing
/// </summary>
public virtual Vector3 position {
get {
return this.value;
}
set {
this.value = value;
neuroid.UpdateState();
}
}
}
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, "sensory neuroid") {
// public SensoryNeuroid(NeuroidNetwork net, int thingId) : base(net, "sensory neuroid") {
public SensoryNeuroid(NanoBrain net, int thingId) : base(net, "sensory neuroid") {
this.receptor = new Receptor {
neuroid = this,
thingId = thingId
@ -17,27 +40,34 @@ public class SensoryNeuroid : Neuroid {
this.AddReceiver(velocityNeuroid);
}
}
public override void UpdateState() {
Vector3 result = receptor.value;
// SensoryNeuroid normally do not have synapses...
// foreach (Synapse synapse in this.synapses.Values) {
// if (synapse.neuroid == null)
// Debug.LogWarning(" disconnected synapse");
// // if (synapse.value != synapse.neuroid.outputValue)
// // Debug.LogWarning("synapse value error");
// // Vector3 direction = synapse.value.normalized;
// // float magnitude = synapse.value.magnitude;
public class Receptor {
public SensoryNeuroid neuroid;
public int thingId;
/// <summary>
/// Local position of the thing
/// </summary>
public virtual Vector3 position {
get {
if (neuroid != null)
return neuroid.synapses[neuroid].value;
else
return Vector3.zero;
}
set {
if (neuroid != null)
neuroid.SetInput(neuroid, value);
// Vector3 direction = synapse.neuroid.outputValue.normalized;
// float magnitude = synapse.neuroid.outputValue.magnitude;
foreach ((Nucleus nucleus, Synapse synapse) in this.synapses) {
Vector3 direction = nucleus.outputValue.normalized;
float magnitude = nucleus.outputValue.magnitude;
magnitude = synapse.weight * Mathf.Pow(magnitude, exponent);
if (inverse)
magnitude = 1 / magnitude;
result += direction * magnitude;
}
if (average && this.synapses.Count > 0)
result /= this.synapses.Count + 1;
this.outputValue = result;
foreach (Neuroid neuroid in this.outputNeuroids)
neuroid.SetInput(this);
this.stale = 0;
}
}
@ -46,12 +76,14 @@ public class VelocityNeuroid : Neuroid {
private Vector3 lastPosition = Vector3.zero;
private float lastValueTime = 0;
public VelocityNeuroid(NeuroidNetwork net) : base(net, "Velocity") {
// public VelocityNeuroid(NeuroidNetwork net) : base(net, "Velocity") {
public VelocityNeuroid(NanoBrain net) : base(net, "Velocity") {
}
protected override void UpdateState() {
public override void UpdateState() {
// Assuming only one synapse for now....
Vector3 currentPosition = this.synapses.First().Value.value;
//Vector3 currentPosition = this.synapses.First().Value.neuroid.outputValue;
Vector3 currentPosition = this.synapses.First().Key.outputValue;
float currentValueTime = Time.time;
float deltaTime = currentValueTime - lastValueTime;
@ -61,7 +93,7 @@ public class VelocityNeuroid : Neuroid {
// No activation function...
this.outputValue = velocity;
foreach (Neuroid receiver in outputNeuroids)
receiver?.SetInput(this, this.outputValue);
receiver?.SetInput(this);
this.stale = 0;
this.lastValueTime = Time.time;

2
Assets/Scenes/Boids/Boids.unity
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@ -371,7 +371,7 @@ MonoBehaviour:
m_Script: {fileID: 11500000, guid: 0464906885ae3494f8fd0314719fb2db, type: 3}
m_Name:
m_EditorClassIdentifier: Assembly-CSharp::SwarmControl
speed: 1
speed: 2
inertia: 0.1
alignmentForce: 5
cohesionForce: 5

22
Assets/Scenes/Boids/Scripts/Boid.cs
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@ -1,16 +1,7 @@
using UnityEngine;
[RequireComponent(typeof(NanoBrain))]
public class Boid : MonoBehaviour {
// public float speed = 0.2f;
// public int neighbourCount = 0;
// public float inertia = 0.2f;
// public float alignmentForce = 1.0f;
// public float cohesionForce = 1.0f;
// public float separationForce = 1.0f;
// public float separationDistance = 0.5f;
// public float bodyForce = 1;
public const int BoundaryType = 1;
public const int BoidType = 2;
@ -21,7 +12,8 @@ public class Boid : MonoBehaviour {
private Bounds innerBounds;
private Bounds outerBounds;
public NeuroidNetwork neuroidNet = new();
//public NeuroidNetwork neuroidNet = new();
public NanoBrain neuroidNet;
public Perception perception;
public Nucleus behaviour;
@ -31,6 +23,8 @@ public class Boid : MonoBehaviour {
public int id;
void Awake() {
neuroidNet = GetComponent<NanoBrain>();
this.id = this.GetInstanceID();
sc = FindFirstObjectByType<SwarmControl>();
@ -48,7 +42,7 @@ public class Boid : MonoBehaviour {
}
void Update() {
Collider[] results = Physics.OverlapSphere(this.transform.position, sc.perceptionDistance);
Collider[] results = Physics.OverlapSphere(this.transform.position, sc.perceptionDistance);
foreach (Collider c in results) {
if (c as CapsuleCollider != null) {
Boid neighbour = c.GetComponentInParent<Boid>();
@ -103,7 +97,9 @@ public class Boid : MonoBehaviour {
}
void OnDrawGizmosSelected() {
Gizmos.DrawWireSphere(transform.position, sc.perceptionDistance);
if (sc == null)
return;
Gizmos.DrawWireSphere(this.transform.position, sc.perceptionDistance);
Gizmos.color = Color.yellow;
Vector3 worldForce = this.transform.TransformDirection(totalForce.outputValue);
Gizmos.DrawRay(transform.position, worldForce * 10);

3
Assets/Scenes/Boids/Scripts/RoamingNucleus.cs
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@ -3,7 +3,8 @@ public class Roaming : Nucleus {
public Neuroid output;
public Roaming(NeuroidNetwork neuroidNet, Perception perception, SwarmControl sc) : base("Roaming nucleus") {
// public Roaming(NeuroidNetwork neuroidNet, Perception perception, SwarmControl sc) : base("Roaming nucleus") {
public Roaming(NanoBrain neuroidNet, Perception perception, SwarmControl sc) : base("Roaming nucleus") {
avoidance = new(neuroidNet, "Avoidance") { inverse = true };
perception.SendPositions(avoidance, 1.0f, 1);

5
Assets/Scenes/Boids/Scripts/SwarmingNucleus.cs
View File

@ -12,7 +12,8 @@ public class Swarming : Nucleus {
public const int BoundaryType = 1;
public const int BoidType = 2;
public Swarming(NeuroidNetwork neuroidNet, Perception perception, SwarmControl sc) : base("Swarming Nucleus") {
// public Swarming(NeuroidNetwork neuroidNet, Perception perception, SwarmControl sc) : base("Swarming Nucleus") {
public Swarming(NanoBrain neuroidNet, Perception perception, SwarmControl sc) : base("Swarming Nucleus") {
this.cohesion = new(neuroidNet, "Cohesion");
perception.SendPositions(this.cohesion, 1.0f, BoidType);
@ -23,7 +24,7 @@ public class Swarming : Nucleus {
perception.SendPositions(this.avoidance);
this.output = new(neuroidNet, "Swarming");
//this.output.GetInputFrom(alignment, sc.alignmentForce);
this.output.GetInputFrom(alignment, sc.alignmentForce);
this.output.GetInputFrom(cohesion, sc.cohesionForce);
this.output.GetInputFrom(avoidance, -sc.avoidanceForce);
}