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Project/Assets/Bullet/Scripts/AttentionSensorComponent.cs

+// using System.Collections;
+// using System.Collections.Generic;
+// using UnityEngine;
+// using Unity.MLAgents.Sensors;
+// using System;
+// using System.Linq;
+
+
+// /// <summary>
+// /// A simple example of a SensorComponent.
+// /// This should be added to the same GameObject as the BasicController
+// /// </summary>
+// public class AttentionSensorComponent : SensorComponent
+// {
+
+//     public int ObservableSize;
+//     public int MaxNumObservables;
+
+//     /// <summary>
+//     /// Creates a BasicSensor.
+//     /// </summary>
+//     /// <returns></returns>
+//     public override ISensor CreateSensor()
+//     {
+//         return new AttentionSensor(transform, ObservableSize, MaxNumObservables);
+//     }
+
+//     /// <inheritdoc/>
+//     public override int[] GetObservationShape()
+//     {
+//         return new[] { MaxNumObservables, ObservableSize, 1};
+//     }
+// }
+
+// /// <summary>
+// /// Simple Sensor implementation that uses a one-hot encoding of the Agent's
+// /// position as the observation.
+// /// </summary>
+// public class AttentionSensor : ISensor
+// {
+//     int m_ObservableSize;
+//     int m_MaxNumObservables;
+//     float[] m_ObservationBuffer;
+//     int m_CurrentNumObservables;
+//     Transform m_AgentTransform;
+
+//     public AttentionSensor(Transform AgentTransform, int ObservableSize, int MaxNumObservables)
+//     {
+//         m_ObservableSize = ObservableSize;
+//         m_MaxNumObservables = MaxNumObservables;
+//         m_AgentTransform = AgentTransform;
+//         m_ObservationBuffer = new float[m_ObservableSize * m_MaxNumObservables];
+//         m_CurrentNumObservables = 0;
+//     }
+
+//     /// <summary>
+//     /// Generate the observations for the sensor.
+//     /// In this case, the observations are all 0 except for a 1 at the position of the agent.
+//     /// </summary>
+//     /// <param name="output"></param>
+//     public int Write(ObservationWriter writer)
+//     {
+//         for (int i = 0; i < m_ObservableSize * m_MaxNumObservables; i++){
+//             writer[i] = m_ObservationBuffer[i];
+//         }
+//         return m_ObservableSize * m_MaxNumObservables;
+//     }
+
+//     public byte[] GetCompressedObservation()
+//     {
+//         return new byte[0];
+//     }
+
+//     public int[] GetObservationShape()
+//     {
+//         return new[] { m_MaxNumObservables, m_ObservableSize,1 };
+//     }
+
+//     /// <inheritdoc/>
+//     public void Update() {
+//         Reset();
+//         var bullets = m_AgentTransform.parent.GetComponentsInChildren<Bullet>();
+//         // Sort by closest :
+//         Array.Sort(bullets , (a, b) => Vector3.Distance(a.transform.position, m_AgentTransform.position) - Vector3.Distance(b.transform.position, m_AgentTransform.position) > 0 ? 1 : -1);
+
+//         // foreach (Bullet b in bullets)
+//         // {
+//         //     b.transform.localScale = 0.5f * new Vector3(1,1,1);
+//         // }
+
+
+
+//         foreach (Bullet b in bullets)
+//         {
+//             if (m_CurrentNumObservables >= m_MaxNumObservables){
+//                 break;
+//             }
+//             m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 0] = (b.transform.position.x - m_AgentTransform.parent.position.x) / 10f;
+//             m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 1] = (b.transform.position.z - m_AgentTransform.parent.position.z) / 10f;
+//             //m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 0] = (b.transform.position.x - m_AgentTransform.position.x) / 10f;
+//             //m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 1] = (b.transform.position.z - m_AgentTransform.position.z) / 10f;
+//             m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 2] = b.transform.forward.x;
+//             m_ObservationBuffer[m_CurrentNumObservables * m_ObservableSize + 3] = b.transform.forward.z;
+//             m_CurrentNumObservables += 1;
+//             // b.transform.localScale = 1f* new Vector3(1,1,1);
+//         }
+
+//     }
+
+//     /// <inheritdoc/>
+//     public void Reset() {
+//         m_CurrentNumObservables = 0;
+//         Array.Clear(m_ObservationBuffer, 0, m_ObservationBuffer.Length);
+//     }
+
+//     public SensorCompressionType GetCompressionType()
+//         {
+//             return SensorCompressionType.None;
+//         }
+
+//     /// <summary>
+//     /// Accessor for the name of the sensor.
+//     /// </summary>
+//     /// <returns>Sensor name.</returns>
+//     public string GetName()
+//     {
+//         return "AttentionSensor";
+//     }
+
+// }

Project/Assets/Bullet/Scripts/AttentionSensorComponent.cs.meta

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Project/Assets/Bullet/Scripts/Bullet.cs

+//Put this script on your blue cube.
+
+using System.Collections;
+using UnityEngine;
+using Unity.MLAgents;
+using Unity.MLAgents.Actuators;
+
+public class Bullet : MonoBehaviour
+{
+    /// <summary>
+    /// The ground. The bounds are used to spawn the elements.
+    /// </summary>
+    public Rigidbody BulletRb;
+    public float speed;
+    void Awake()
+    {
+        BulletRb = GetComponent<Rigidbody>();
+        //BulletRb.AddForce(20f*transform.forward, ForceMode.VelocityChange);
+    }
+
+    public void FixedUpdate()
+    {
+       transform.position += transform.forward * speed;
+    }
+    public void OnCollisionEnter(Collision c)
+    {
+        if (c.gameObject.CompareTag("wall")){
+            //gameObject.SetActive(false);
+            Destroy(gameObject);
+        }
+    }
+}

Project/Assets/Bullet/Scripts/Bullet.cs.meta

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Project/Assets/Bullet/Scripts/BulletAgent.cs

+//Put this script on your blue cube.
+
+using System.Collections;
+using UnityEngine;
+using Unity.MLAgents;
+using Unity.MLAgents.Actuators;
+
+public class BulletAgent : MonoBehaviour
+{
+    /// <summary>
+    /// The ground. The bounds are used to spawn the elements.
+    /// </summary>
+    public GameObject ground;
+
+    public GameObject area;
+
+    public GameObject bullet;
+    Rigidbody m_BulletRb;
+
+    float m_BulletTime;
+    /// <summary>
+    /// The area bounds.
+    /// </summary>
+    [HideInInspector]
+    public Bounds areaBounds;
+    public float rad;
+
+    BulletSettings m_BulletSettings;
+
+    float m_x;
+    float m_z;
+    float radius;
+    float m_currX;
+    float m_currZ;
+    Vector3 m_center;
+    public bool useVectorObs;
+
+    //Rigidbody m_AgentRb;  //cached on initialization
+    Material m_GroundMaterial; //cached on Awake()
+
+    /// <summary>
+    /// We will be changing the ground material based on success/failue
+    /// </summary>
+    Renderer m_GroundRenderer;
+
+    EnvironmentParameters m_ResetParams;
+
+    void Awake()
+    {
+        m_BulletSettings = FindObjectOfType<BulletSettings>();
+        areaBounds = ground.GetComponent<Collider>().bounds;
+        m_BulletRb = bullet.GetComponent<Rigidbody>();
+        //area = GetComponent<BulletArea>();
+        m_x = areaBounds.extents.x;
+        m_z = areaBounds.extents.z;
+        m_currX = area.transform.position.x;
+        m_currZ = area.transform.position.z + m_z - rad;
+        var angle = (Random.Range(0f,360f) * Mathf.PI/ 180f);
+        var x = Mathf.Cos(angle) * (m_currX - area.transform.position.x) - Mathf.Sin(angle) * (m_currZ - area.transform.position.z) + area.transform.position.x;;
+        var z = Mathf.Sin(angle) * (m_currX - area.transform.position.x) + Mathf.Cos(angle) * (m_currZ - area.transform.position.z) + area.transform.position.z;
+        m_currX = x;
+        m_currZ = z;
+        m_center = new Vector3(area.transform.position.x, 0.5f, area.transform.position.z);
+        m_BulletTime = 0f;
+    }
+
+
+        // Cache the agent rigidbody
+     //   m_AgentRb = GetComponent<Rigidbody>();
+        // Cache the block rigidbody
+        // Get the ground's bounds
+        // Get the ground renderer so we can change the material when a goal is scored
+
+
+    public void FixedUpdate()
+    {
+        if (Time.time > m_BulletTime + 0.03f)
+        {
+            //var x = Random.Range(-1f * m_x, m_x) + area.transform.position.x;
+            //var z = Random.Range(-1f * m_z, m_z) + area.transform.position.z;
+            var r = Random.Range(0f, 360f);
+            var ra = Random.Range(0, 2);
+            var dir = -1f;
+            if (ra == 1)
+            {
+                dir = 1f;
+            }
+            var angle = dir * (5f * Mathf.PI/ 180f);
+            var x = Mathf.Cos(angle) * (m_currX - area.transform.position.x) - Mathf.Sin(angle) * (m_currZ - area.transform.position.z) + area.transform.position.x;;
+            var z = Mathf.Sin(angle) * (m_currX - area.transform.position.x) + Mathf.Cos(angle) * (m_currZ - area.transform.position.z) + area.transform.position.z;
+            var pos = new Vector3(x, 0.5f, z);
+
+            Quaternion rotation = Quaternion.Euler(0, r, 0);
+            //Quaternion rotation = Quaternion.LookRotation(m_center - pos);
+            var ob = Instantiate(m_BulletRb, pos, rotation, area.transform);
+            m_currX = x;
+            m_currZ = z;
+    //        ob.GetComponent<Rigidbody>().AddForce(20f*ob.transform.forward, ForceMode.VelocityChange);
+            m_BulletTime = Time.time;
+
+        }
+    }
+}

Project/Assets/Bullet/Scripts/BulletAgent.cs.meta

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Project/Assets/Bullet/Scripts/BulletSettings.cs

+using UnityEngine;
+
+public class BulletSettings : MonoBehaviour
+{
+    /// <summary>
+    /// The "walking speed" of the agents in the scene.
+    /// </summary>
+    public float agentRunSpeed;
+
+    /// <summary>
+    /// The agent rotation speed.
+    /// Every agent will use this setting.
+    /// </summary>
+    public float agentRotationSpeed;
+
+    /// <summary>
+    /// The spawn area margin multiplier.
+    /// ex: .9 means 90% of spawn area will be used.
+    /// .1 margin will be left (so players don't spawn off of the edge).
+    /// The higher this value, the longer training time required.
+    /// </summary>
+    public float spawnAreaMarginMultiplier;
+
+}

Project/Assets/Bullet/Scripts/BulletSettings.cs.meta

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Project/Assets/Bullet/Scripts/DodgeAgent.cs

+//Put this script on your blue cube.
+
+using System.Collections;
+using UnityEngine;
+using Unity.MLAgents;
+using Unity.MLAgents.Actuators;
+using Unity.MLAgents.Sensors;
+
+public class DodgeAgent : Agent
+{
+    /// <summary>
+    /// The ground. The bounds are used to spawn the elements.
+    /// </summary>
+    public GameObject ground;
+
+    public GameObject area;
+
+    /// <summary>
+    /// The area bounds.
+    /// </summary>
+    [HideInInspector]
+    public Bounds areaBounds;
+
+    BulletSettings m_BulletSettings;
+
+
+    Rigidbody m_AgentRb;  //cached on initialization
+    Material m_GroundMaterial; //cached on Awake()
+
+    /// <summary>
+    /// We will be changing the ground material based on success/failue
+    /// </summary>
+    Renderer m_GroundRenderer;
+
+    EnvironmentParameters m_ResetParams;
+
+    BufferSensorComponent m_BufferSensor;
+
+    void Awake()
+    {
+        m_BulletSettings = FindObjectOfType<BulletSettings>();
+    }
+
+    public override void Initialize()
+    {
+        m_BufferSensor = GetComponent<BufferSensorComponent>();
+
+        // Cache the agent rigidbody
+        m_AgentRb = GetComponent<Rigidbody>();
+        // Cache the block rigidbody
+        // Get the ground's bounds
+        areaBounds = ground.GetComponent<Collider>().bounds;
+        // Get the ground renderer so we can change the material when a goal is scored
+        m_GroundRenderer = ground.GetComponent<Renderer>();
+        // Starting material
+        m_GroundMaterial = m_GroundRenderer.material;
+
+        m_ResetParams = Academy.Instance.EnvironmentParameters;
+
+        SetResetParameters();
+    }
+
+    /// <summary>
+    /// Use the ground's bounds to pick a random spawn position.
+    /// </summary>
+    public Vector3 GetRandomSpawnPos()
+    {
+        var foundNewSpawnLocation = false;
+        var randomSpawnPos = Vector3.zero;
+        while (foundNewSpawnLocation == false)
+        {
+            var randomPosX = Random.Range(-areaBounds.extents.x * m_BulletSettings.spawnAreaMarginMultiplier,
+                areaBounds.extents.x * m_BulletSettings.spawnAreaMarginMultiplier);
+
+            var randomPosZ = Random.Range(-areaBounds.extents.z * m_BulletSettings.spawnAreaMarginMultiplier,
+                areaBounds.extents.z * m_BulletSettings.spawnAreaMarginMultiplier);
+            randomSpawnPos = ground.transform.position + new Vector3(randomPosX, 1f, randomPosZ);
+            if (Physics.CheckBox(randomSpawnPos, new Vector3(2.5f, 0.01f, 2.5f)) == false)
+            {
+                foundNewSpawnLocation = true;
+            }
+        }
+        return randomSpawnPos;
+    }
+
+    public override void CollectObservations(VectorSensor sensor)
+    {
+
+        sensor.AddObservation((transform.position.x - area.transform.position.x) / 10f);
+        sensor.AddObservation((transform.position.z - area.transform.position.z) / 10f);
+
+
+        // Collect observation about the 20 closest Bullets
+        var bullets = transform.parent.GetComponentsInChildren<Bullet>();
+        // Sort by closest :
+        System.Array.Sort(bullets, (a, b) => (Vector3.Distance(a.transform.position, transform.position)).CompareTo(Vector3.Distance(b.transform.position, transform.position)));
+        int numBulletAdded = 0;
+
+        // foreach (Bullet b in bullets)
+        // {
+        //     b.transform.localScale = new Vector3(1, 1, 1);
+        // }
+
+        foreach (Bullet b in bullets)
+        {
+            if (numBulletAdded >= 20)
+            {
+                break;
+            }
+
+            float[] bulletObservation = new float[]{
+                (b.transform.position.x - transform.position.x) / 10f, // relative position
+                (b.transform.position.z - transform.position.z) / 10f,
+                b.transform.forward.x,
+                b.transform.forward.z
+            };
+            numBulletAdded += 1;
+
+            m_BufferSensor.AppendObservation(bulletObservation);
+
+            // b.transform.localScale = new Vector3(2, 2, 2);
+        };
+
+
+    }
+    /// <summary>
+    /// Called every step of the engine. Here the agent takes an action.
+    /// </summary>
+    public override void OnActionReceived(ActionBuffers actionBuffers)
+
+    {
+        var forwardForce = Mathf.Clamp(actionBuffers.ContinuousActions[0], -1f, 1f);
+        var lateralForce = Mathf.Clamp(actionBuffers.ContinuousActions[1], -1f, 1f);
+        var rotationForce =0.0f;// Mathf.Clamp(actionBuffers.ContinuousActions[2], -1f, 1f);
+
+        //Vector3 dirToGo = transform.forward * forwardForce + transform.right * lateralForce;
+        Vector3 rotateDir = transform.up * rotationForce;
+
+        transform.Rotate(rotateDir, Time.fixedDeltaTime * 200f);
+        Vector3 dirToGo = new Vector3(1, 0, 0) * forwardForce + new Vector3(0, 0, 1) * lateralForce;
+        m_AgentRb.AddForce(dirToGo * m_BulletSettings.agentRunSpeed,
+            ForceMode.VelocityChange);
+        //Vector3 dirToCenter = new Vector3((transform.position.x - area.transform.position.x) / 10f, 0f, (transform.position.z - area.transform.position.z) / 10f);
+        //AddReward(.001f / (dirToCenter.magnitude + .0000001f));
+        AddReward(.001f);
+
+    }
+
+    public override void Heuristic(in ActionBuffers actionsOut)
+    {
+        var continuousActionsOut = actionsOut.ContinuousActions;
+        continuousActionsOut[0] = 0f;
+        continuousActionsOut[1] = 0f;
+        continuousActionsOut[2] = 0f;
+        if (Input.GetKey(KeyCode.D))
+        {
+            continuousActionsOut[2] = 1f;
+        }
+        else if (Input.GetKey(KeyCode.W))
+        {
+            continuousActionsOut[0] = 1f;
+        }
+        else if (Input.GetKey(KeyCode.A))
+        {
+            continuousActionsOut[2] = -1f;
+        }
+        else if (Input.GetKey(KeyCode.S))
+        {
+            continuousActionsOut[0] = -1f;
+        }
+        else if (Input.GetKey(KeyCode.Q))
+        {
+            continuousActionsOut[1] = -1f;
+        }
+        else if (Input.GetKey(KeyCode.E))
+        {
+            continuousActionsOut[1] = 1f;
+        }
+
+    }
+
+    void OnCollisionEnter(Collision collision)
+    {
+        if (collision.gameObject.CompareTag("badFood") || collision.gameObject.CompareTag("wall"))
+        {
+            SetReward(0f);
+            EndEpisode();
+        }
+    }
+
+    /// <summary>
+    /// In the editor, if "Reset On Done" is checked then AgentReset() will be
+    /// called automatically anytime we mark done = true in an agent script.
+    /// </summary>
+    public override void OnEpisodeBegin()
+    {
+        // var rotation = Random.Range(0, 4);
+        // var rotationAngle = rotation * 90f;
+        // area.transform.Rotate(new Vector3(0f, rotationAngle, 0f));
+
+        transform.position = GetRandomSpawnPos();//
+        m_AgentRb.velocity = Vector3.zero;
+        m_AgentRb.angularVelocity = Vector3.zero;
+
+        SetResetParameters();
+    }
+
+    public void SetGroundMaterialFriction()
+    {
+        var groundCollider = ground.GetComponent<Collider>();
+
+        groundCollider.material.dynamicFriction = m_ResetParams.GetWithDefault("dynamic_friction", 0);
+        groundCollider.material.staticFriction = m_ResetParams.GetWithDefault("static_friction", 0);
+    }
+
+
+    void SetResetParameters()
+    {
+        //SetGroundMaterialFriction();
+    }
+}

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results/Bullet-New/Dodge/events.out.tfevents.1613677476.vincentpierre-0W0M.68971.0

+�K"	{�8���A
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+�
+Hyperparameters/text_summaryB�
B�	trainer_type:	ppo
+	hyperparameters:	
+	  batch_size:	1024
+	  buffer_size:	10240
+	  learning_rate:	0.0003
+	  beta:	0.005
+	  epsilon:	0.2
+	  lambd:	0.95
+	  num_epoch:	3
+	  learning_rate_schedule:	linear
+	network_settings:	
+	  normalize:	True
+	  hidden_units:	128
+	  num_layers:	2
+	  vis_encode_type:	simple
+	  memory:	None
+	reward_signals:	
+	  extrinsic:	
+	    gamma:	0.99
+	    strength:	1.0
+	init_path:	None
+	keep_checkpoints:	5
+	checkpoint_interval:	500000
+	max_steps:	50000000
+	time_horizon:	64
+	summary_freq:	100000
+	threaded:	True
+	self_play:	None
+	behavioral_cloning:	NoneJ
+
+text�;

results/Bullet-New/configuration.yaml

+default_settings: null
+behaviors:
+  Dodge:
+    trainer_type: ppo
+    hyperparameters:
+      batch_size: 1024
+      buffer_size: 10240
+      learning_rate: 0.0003
+      beta: 0.005
+      epsilon: 0.2
+      lambd: 0.95
+      num_epoch: 3
+      learning_rate_schedule: linear
+    network_settings:
+      normalize: true
+      hidden_units: 128
+      num_layers: 2
+      vis_encode_type: simple
+      memory: null
+    reward_signals:
+      extrinsic:
+        gamma: 0.99
+        strength: 1.0
+    init_path: null
+    keep_checkpoints: 5
+    checkpoint_interval: 500000
+    max_steps: 50000000
+    time_horizon: 64
+    summary_freq: 100000
+    threaded: true
+    self_play: null
+    behavioral_cloning: null
+env_settings:
+  env_path: null
+  env_args: null
+  base_port: 5005
+  num_envs: 1
+  seed: -1
+engine_settings:
+  width: 84
+  height: 84
+  quality_level: 5
+  time_scale: 20
+  target_frame_rate: -1
+  capture_frame_rate: 60
+  no_graphics: false
+environment_parameters: null
+checkpoint_settings:
+  run_id: Bullet-New
+  initialize_from: null
+  load_model: false
+  resume: false
+  force: true
+  train_model: false
+  inference: false
+  results_dir: results
+torch_settings:
+  device: null
+debug: false

results/Bullet-New/run_logs/Player-0.log

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results/Bullet-New/run_logs/Player-1.log

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results/Bullet-New/run_logs/Player-2.log

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results/Bullet-New/run_logs/Player-4.log

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+ 
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+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so
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+Setting up 8 worker threads for Enlighten.
+  Thread -> id: 7000098ba000 -> priority: 1 
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results/Bullet-New/run_logs/Player-5.log

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+Initialize engine version: 2018.4.20f1 (008688490035)
+GfxDevice: creating device client; threaded=1
+Initializing Metal device caps: AMD Radeon Pro 5500M
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+Setting up 8 worker threads for Enlighten.
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results/Bullet-New/run_logs/Player-6.log

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+Initialize engine version: 2018.4.20f1 (008688490035)
+GfxDevice: creating device client; threaded=1
+Initializing Metal device caps: AMD Radeon Pro 5500M
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+(Filename:  Line: 294)
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+Setting up 8 worker threads for Enlighten.
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results/Bullet-New/run_logs/Player-7.log

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+Initialize engine version: 2018.4.20f1 (008688490035)
+GfxDevice: creating device client; threaded=1
+Initializing Metal device caps: AMD Radeon Pro 5500M
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+- Completed reload, in  0.143 seconds
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+(Filename:  Line: 294)
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+Setting up 8 worker threads for Enlighten.
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results/Bullet-New/run_logs/Player-8.log

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+Initialize engine version: 2018.4.20f1 (008688490035)
+GfxDevice: creating device client; threaded=1
+Initializing Metal device caps: AMD Radeon Pro 5500M
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+- Completed reload, in  0.142 seconds
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+(Filename:  Line: 294)
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+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
+Setting up 8 worker threads for Enlighten.
+  Thread -> id: 70000b9d0000 -> priority: 1 
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results/Bullet-New/run_logs/Player-9.log

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+Initialize engine version: 2018.4.20f1 (008688490035)
+GfxDevice: creating device client; threaded=1
+Initializing Metal device caps: AMD Radeon Pro 5500M
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+- Completed reload, in  0.145 seconds
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+ 
+(Filename:  Line: 294)
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+The referenced script on this Behaviour (Game Object 'EventSystem') is missing!
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+UnloadTime: 0.643213 ms
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+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so.bundle
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so.dylib
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so.bundle
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libcoreclr.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so.dylib
+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
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+Fallback handler could not load library /Users/vincentpierre/Downloads/ml-agents/envs/mantas-bullet.app/Contents/Frameworks/MonoEmbedRuntime/osx/libdl.so
+Setting up 8 worker threads for Enlighten.
+  Thread -> id: 700004ff1000 -> priority: 1 
+  Thread -> id: 7000050f7000 -> priority: 1 
+  Thread -> id: 700005074000 -> priority: 1 
+  Thread -> id: 700005303000 -> priority: 1 
+  Thread -> id: 70000517a000 -> priority: 1 
+  Thread -> id: 7000051fd000 -> priority: 1 
+  Thread -> id: 700005280000 -> priority: 1 
+  Thread -> id: 700005386000 -> priority: 1 

results/Bullet-New/run_logs/timers.json

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results/Bullet-New/run_logs/training_status.json

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