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about to implement orientation cube

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Hunter-Unity 5 年前
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共有 18 个文件被更改，包括 3180 次插入 和 0 次删除
  1. 297
      Project/Assets/ML-Agents/Examples/SharedAssets/Prefabs/OrientationCube.prefab
  2. 7
      Project/Assets/ML-Agents/Examples/SharedAssets/Prefabs/OrientationCube.prefab.meta
  3. 295
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/AvgCenterOfMass.cs
  4. 11
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/AvgCenterOfMass.cs.meta
  5. 28
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/RagdollHelpers.cs
  6. 3
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/RagdollHelpers.cs.meta
  7. 26
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/TransformExtensions.cs
  8. 3
      Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/TransformExtensions.cs.meta
  9. 1001
      Project/Assets/ML-Agents/Examples/Walker/Prefabs/WalkerPairDynamic.prefab
  10. 7
      Project/Assets/ML-Agents/Examples/Walker/Prefabs/WalkerPairDynamic.prefab.meta
  11. 865
      Project/Assets/ML-Agents/Examples/Walker/Scenes/WalkerDynamic.unity
  12. 9
      Project/Assets/ML-Agents/Examples/Walker/Scenes/WalkerDynamic.unity.meta
  13. 249
      Project/Assets/ML-Agents/Examples/Walker/Scripts/WalkerAgentDynamic.cs
  14. 12
      Project/Assets/ML-Agents/Examples/Walker/Scripts/WalkerAgentDynamic.cs.meta
  15. 8
      Project/Assets/Puppo.meta
  16. 351
      config/trainer_config.yaml
  17. 8
      Project/Assets/Puppo/Race Day.meta

297
Project/Assets/ML-Agents/Examples/SharedAssets/Prefabs/OrientationCube.prefab
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Project/Assets/ML-Agents/Examples/SharedAssets/Prefabs/OrientationCube.prefab.meta
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295
Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/AvgCenterOfMass.cs
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using System.Collections.Generic;
using UnityEngine;
/// <summary>
/// Used for visualizing the average center of mass of a ragdoll
/// </summary>
[DisallowMultipleComponent]
[ExecuteInEditMode]
public class AvgCenterOfMass : MonoBehaviour
{
/// <summary>
/// Enable to show a green spehere at the current center of mass.
/// </summary>
[Tooltip("Enable to show a green spehere at the current center of mass.")]
public bool showCOMGizmos = true;
public Vector3 avgCOMWorldSpace;
public Color avgCOMColor = Color.green;
public Color bodyPartCOMColor = Color.yellow;
List<Rigidbody> rbList = new List<Rigidbody>();
public float totalMass;
[Tooltip("Visualize Relative Pos")]
public bool showBPPosRelToBody;
public bool useTransformPoint = true;
public bool useTransformVector;
public bool useTransformDir;
public bool showRBPos;
public bool showRelPosVectorOnly;
public bool showInverseTransformPointUnscaledRelToBody;
public bool showInverseTransformPointRelToBody;
public bool showInverseTransformVectorRelToBody;
public bool showInverseTransformDirRelToBody;
public Transform body_T;
void Start()
{
SetUpRigidbodies();
}
void SetUpRigidbodies()
{
rbList.Clear();
totalMass = 0;
foreach(var item in GetComponentsInChildren<Rigidbody>())
{
rbList.Add(item);
totalMass += item.mass;
}
}
// void FixedUpdate()
// {
// if(Application.isPlaying)
// {
// avgCOMWorldSpace = Vector3.zero;
// foreach(var item in rbList)
// {
// if (item)
// {
// avgCOMWorldSpace += item.worldCenterOfMass;
// }
// }
// //DRAW AVG GIZMOS
// avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
// }
// }
void FixedUpdate()
{
if(Application.isPlaying)
{
// avgCOMWorldSpace = Vector3.zero;
// foreach(var item in rbList)
// {
// if (item)
// {
// avgCOMWorldSpace += item.worldCenterOfMass;
// }
// }
// //DRAW AVG GIZMOS
// avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
Vector3 CoM = Vector3.zero;
float c = 0f;
foreach(var item in rbList)
{
CoM += item.worldCenterOfMass * item.mass;
c += item.mass;
}
avgCOMWorldSpace = CoM/c;
// CoM /= c;
if (showBPPosRelToBody)
{
var pos = body_T.position;
Matrix4x4 bodyMatrix = body_T.localToWorldMatrix;
// get position from the last column
var bodyPos = new Vector3(bodyMatrix[0,3], bodyMatrix[1,3], bodyMatrix[2,3]);
Debug.DrawRay(bodyPos, Vector3.up, Color.yellow,Time.fixedDeltaTime);
foreach (var rb in rbList)
{
if (showRBPos)
{
Debug.DrawRay(rb.position, Vector3.up, Color.green,Time.fixedDeltaTime);
}
if (rb.transform != body_T)
{
if (showRelPosVectorOnly)
{
var relPosVector = rb.position - body_T.position;
// Debug.DrawRay(body_T.position + body_T.InverseTransformPoint(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
Debug.DrawRay(body_T.position + relPosVector, Vector3.up, Color.red,Time.fixedDeltaTime);
// Vector3 currentLocalPosRelToMatrix = bodyMatrix.inverse.MultiplyPoint(rb.position);
Vector3 currentLocalPosRelToMatrix = bodyMatrix.inverse.MultiplyVector(rb.position - bodyPos);
Debug.DrawRay(body_T.position + currentLocalPosRelToMatrix, Vector3.up, Color.green,Time.fixedDeltaTime);
}
if (showInverseTransformPointUnscaledRelToBody)
{
// Debug.DrawRay(body_T.position + body_T.InverseTransformPoint(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
Debug.DrawRay(body_T.position + body_T.InverseTransformPointUnscaled(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
}
if (showInverseTransformPointRelToBody)
{
// Debug.DrawRay(body_T.position + body_T.InverseTransformPoint(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
Debug.DrawRay(body_T.position + body_T.InverseTransformPoint(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
}
if (showInverseTransformDirRelToBody)
{
Debug.DrawRay(body_T.InverseTransformDirection(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
}
if (showInverseTransformVectorRelToBody)
{
Debug.DrawRay(body_T.position + body_T.InverseTransformVector(rb.position - body_T.position), Vector3.up, Color.red,Time.fixedDeltaTime);
}
// var localPosRelToBody = body.InverseTransformPoint(rb.position);
// Debug.DrawRay(body_T.position + body_T.InverseTransformPoint(rb.position), Vector3.up, Color.red,Time.fixedDeltaTime);
// Debug.DrawRay(body_T.position + rb.transform.TransformVector(rb.transform.localPosition), Vector3.up, Color.cyan,Time.fixedDeltaTime);
// Debug.DrawRay(rb.transform.TransformPoint(rb.position), Vector3.up, Color.green,Time.fixedDeltaTime);
// Debug.DrawRay(body_T.position + body_T.InverseTransformVector(rb.transform.position), Vector3.up, Color.red,Time.fixedDeltaTime);
// Debug.DrawRay(body_T.position + body_T.InverseTransformDirection(rb.transform.position), Vector3.up, Color.red,Time.fixedDeltaTime);
// Debug.DrawRay(body_T.position + body_T.TransformPoint(rb.transform.localPosition), Vector3.up, Color.red,Time.fixedDeltaTime);
if (useTransformPoint)
{
}
else if (useTransformVector)
{
}
else if (useTransformDir)
{
}
}
}
}
}
}
private void OnDrawGizmosSelected()
{
if(!Application.isPlaying)
{
if (showCOMGizmos)
{
Vector3 CoM = Vector3.zero;
float c = 0f;
// avgCOMWorldSpace = Vector3.zero;
//SHOW BODY PART GIZMOS
foreach(var item in rbList)
{
// if (item)
// {
Gizmos.color = bodyPartCOMColor;
float drawCOMRadius = item.mass/totalMass;
Gizmos.DrawSphere(item.worldCenterOfMass, drawCOMRadius);
// Gizmos.DrawWireSphere(item.worldCenterOfMass, drawCOMRadius);
CoM += item.worldCenterOfMass * item.mass;
c += item.mass;
// avgCOMWorldSpace += item.worldCenterOfMass;
// }
}
//DRAW AVG GIZMOS
avgCOMWorldSpace = CoM/c;
// avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
float avgCOMRadius = 0.1f; //radius of gizmo
Gizmos.color = avgCOMColor;
Gizmos.DrawSphere(avgCOMWorldSpace, avgCOMRadius);
}
}
else
{
if (showCOMGizmos)
{
// avgCOMWorldSpace = Vector3.zero;
//SHOW BODY PART GIZMOS
foreach(var item in rbList)
{
// if (item)
// {
Gizmos.color = bodyPartCOMColor;
float drawCOMRadius = item.mass/totalMass;
Gizmos.DrawSphere(item.worldCenterOfMass, drawCOMRadius);
// Gizmos.DrawWireSphere(item.worldCenterOfMass, drawCOMRadius);
// avgCOMWorldSpace += item.worldCenterOfMass;
// }
}
//DRAW AVG GIZMOS
// avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
float avgCOMGizmoRadius = 0.1f; //radius of gizmo
Gizmos.color = avgCOMColor;
Gizmos.DrawSphere(avgCOMWorldSpace, avgCOMGizmoRadius);
}
}
}
// {
// if(!Application.isPlaying)
// {
// if (showCOMGizmos)
// {
// avgCOMWorldSpace = Vector3.zero;
// //SHOW BODY PART GIZMOS
// foreach(var item in rbList)
// {
// if (item)
// {
// Gizmos.color = bodyPartCOMColor;
// float drawCOMRadius = item.mass/totalMass;
// Gizmos.DrawWireSphere(item.worldCenterOfMass, drawCOMRadius);
// avgCOMWorldSpace += item.worldCenterOfMass;
// }
// }
// //DRAW AVG GIZMOS
// avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
// float avgCOMRadius = 0.1f; //radius of gizmo
// Gizmos.color = avgCOMColor;
// Gizmos.DrawSphere(avgCOMWorldSpace, avgCOMRadius);
// }
// }
// else
// {
// if (showCOMGizmos)
// {
// // avgCOMWorldSpace = Vector3.zero;
// //SHOW BODY PART GIZMOS
// foreach(var item in rbList)
// {
// if (item)
// {
// Gizmos.color = bodyPartCOMColor;
// float drawCOMRadius = item.mass/totalMass;
// Gizmos.DrawWireSphere(item.worldCenterOfMass, drawCOMRadius);
// // avgCOMWorldSpace += item.worldCenterOfMass;
// }
// }
// //DRAW AVG GIZMOS
// // avgCOMWorldSpace /= rbList.Count; //divide by num of rb's to get avg in WORLD space
// float avgCOMGizmoRadius = 0.1f; //radius of gizmo
// Gizmos.color = avgCOMColor;
// Gizmos.DrawSphere(avgCOMWorldSpace, avgCOMGizmoRadius);
// }
// }
// }
}

11
Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/AvgCenterOfMass.cs.meta
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28
Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/RagdollHelpers.cs
查看文件


using UnityEngine;
namespace MLAgentsExamples
{
/// <summary>
/// This class contains logic for common ragdoll operations & helper methods.
/// </summary>
public static class RagdollHelpers
{
/// <summary>
//Get Joint Rotation Relative to the Connected Rigidbody
//We want to collect this info because it is the actual rotation, not the "target rotation"
//..because when the joint is weak, the target rotation will be much different than the actual rotation
/// </summary>
public static Quaternion GetJointRotation(ConfigurableJoint joint)
{
Quaternion rotDiff = Quaternion.Inverse(joint.connectedBody.transform.rotation) * joint.transform.rotation;
return(rotDiff);
// return(Quaternion.FromToRotation(joint.axis, joint.connectedBody.transform.rotation.eulerAngles));
}
public static Quaternion GetRotationDelta(Quaternion r1, Quaternion r2)
{
Quaternion rotDiff = Quaternion.Inverse(r1) * r2;
return(rotDiff);
}
}
}

3
Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/RagdollHelpers.cs.meta
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26
Project/Assets/ML-Agents/Examples/SharedAssets/Scripts/TransformExtensions.cs
查看文件


using UnityEngine;
/// <summary>
/// A Transform Extension that ignores scale for TransformPoint operations.
/// </summary>
public static class TransformExtensions
{
/// <summary>
/// Transform position from world space to local space unscaled.
/// </summary>
public static Vector3 TransformPointUnscaled(this Transform transform, Vector3 position)
{
var localToWorldMatrix = Matrix4x4.TRS(transform.position, transform.rotation, Vector3.one);
return localToWorldMatrix.MultiplyPoint3x4(position);
}
/// <summary>
/// Transform position from local space to world space unscaled.
/// </summary>
public static Vector3 InverseTransformPointUnscaled(this Transform transform, Vector3 position)
{
var worldToLocalMatrix = Matrix4x4.TRS(transform.position, transform.rotation, Vector3.one).inverse;
return worldToLocalMatrix.MultiplyPoint3x4(position);
}
}

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Project/Assets/ML-Agents/Examples/Walker/Scenes/WalkerDynamic.unity.meta
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249
Project/Assets/ML-Agents/Examples/Walker/Scripts/WalkerAgentDynamic.cs
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using MLAgentsExamples;
using UnityEngine;
using Unity.MLAgents;
using Unity.MLAgentsExamples;
using Unity.MLAgents.Sensors;
public class WalkerAgentDynamic : Agent
{
[Header("Specific to Walker")]
[Header("Target To Walk Towards")]
[Space(10)]
public Transform target;
//ORIENTATION
Vector3 m_WalkDir;
Quaternion m_WalkDirLookRot;
Matrix4x4 m_worldPosMatrix;
public Transform hips;
public Transform chest;
public Transform spine;
public Transform head;
public Transform thighL;
public Transform shinL;
public Transform footL;
public Transform thighR;
public Transform shinR;
public Transform footR;
public Transform armL;
public Transform forearmL;
public Transform handL;
public Transform armR;
public Transform forearmR;
public Transform handR;
JointDriveController m_JdController;
Rigidbody m_HipsRb;
Rigidbody m_ChestRb;
Rigidbody m_SpineRb;
EnvironmentParameters m_ResetParams;
public override void Initialize()
{
m_JdController = GetComponent<JointDriveController>();
m_JdController.SetupBodyPart(hips);
m_JdController.SetupBodyPart(chest);
m_JdController.SetupBodyPart(spine);
m_JdController.SetupBodyPart(head);
m_JdController.SetupBodyPart(thighL);
m_JdController.SetupBodyPart(shinL);
m_JdController.SetupBodyPart(footL);
m_JdController.SetupBodyPart(thighR);
m_JdController.SetupBodyPart(shinR);
m_JdController.SetupBodyPart(footR);
m_JdController.SetupBodyPart(armL);
m_JdController.SetupBodyPart(forearmL);
m_JdController.SetupBodyPart(handL);
m_JdController.SetupBodyPart(armR);
m_JdController.SetupBodyPart(forearmR);
m_JdController.SetupBodyPart(handR);
m_HipsRb = hips.GetComponent<Rigidbody>();
m_ChestRb = chest.GetComponent<Rigidbody>();
m_SpineRb = spine.GetComponent<Rigidbody>();
m_ResetParams = Academy.Instance.EnvironmentParameters;
SetResetParameters();
}
/// <summary>
/// Add relevant information on each body part to observations.
/// </summary>
public void CollectObservationBodyPart(BodyPart bp, VectorSensor sensor)
{
//GROUND CHECK
sensor.AddObservation(bp.groundContact.touchingGround ? 1 : 0); // Is this bp touching the ground
//RELATIVE RB VELOCITY
var velocityRelativeToLookRotationToTarget = m_worldPosMatrix.inverse.MultiplyVector(bp.rb.velocity);
sensor.AddObservation(velocityRelativeToLookRotationToTarget);
//RELATIVE RB ANGULAR VELOCITY
var angularVelocityRelativeToLookRotationToTarget = m_worldPosMatrix.inverse.MultiplyVector(bp.rb.angularVelocity);
sensor.AddObservation(angularVelocityRelativeToLookRotationToTarget);
// sensor.AddObservation(rb.velocity);
// sensor.AddObservation(rb.angularVelocity);
// var localPosRelToHips = hips.InverseTransformPoint(rb.position);
// sensor.AddObservation(localPosRelToHips);
sensor.AddObservation(hips.InverseTransformPointUnscaled(bp.rb.position));
// if (bp.rb.transform != hips && bp.rb.transform != handL && bp.rb.transform != handR &&
// bp.rb.transform != footL && bp.rb.transform != footR && bp.rb.transform != head)
if (bp.rb.transform != hips && bp.rb.transform != handL && bp.rb.transform != handR &&
bp.rb.transform != footL && bp.rb.transform != footR)
{
sensor.AddObservation(RagdollHelpers.GetJointRotation(bp.joint));
// sensor.AddObservation(bp.currentXNormalizedRot);
// sensor.AddObservation(bp.currentYNormalizedRot);
// sensor.AddObservation(bp.currentZNormalizedRot);
sensor.AddObservation(bp.currentStrength / m_JdController.maxJointForceLimit);
}
}
// /// <summary>
// /// Add relevant information on each body part to observations.
// /// </summary>
// public void CollectObservationBodyPart(BodyPart bp, VectorSensor sensor)
// {
// var rb = bp.rb;
// sensor.AddObservation(bp.groundContact.touchingGround ? 1 : 0); // Is this bp touching the ground
// sensor.AddObservation(rb.velocity);
// sensor.AddObservation(rb.angularVelocity);
// var localPosRelToHips = hips.InverseTransformPoint(rb.position);
// sensor.AddObservation(localPosRelToHips);
//
// if (bp.rb.transform != hips && bp.rb.transform != handL && bp.rb.transform != handR &&
// bp.rb.transform != footL && bp.rb.transform != footR && bp.rb.transform != head)
// {
// sensor.AddObservation(bp.currentXNormalizedRot);
// sensor.AddObservation(bp.currentYNormalizedRot);
// sensor.AddObservation(bp.currentZNormalizedRot);
// sensor.AddObservation(bp.currentStrength / m_JdController.maxJointForceLimit);
// }
// }
/// <summary>
/// Loop over body parts to add them to observation.
/// </summary>
public override void CollectObservations(VectorSensor sensor)
{
m_JdController.GetCurrentJointForces();
// Update pos to target
m_WalkDir = target.position - hips.position;
//FACING DIR
m_WalkDirLookRot = Quaternion.LookRotation(m_WalkDir);
sensor.AddObservation(RagdollHelpers.GetRotationDelta(m_WalkDirLookRot, hips.rotation));
// m_TargetDirMatrix = Matrix4x4.TRS(Vector3.zero, m_LookRotation, Vector3.one);
//ORIENTATION MATRIX
Vector3 worldPosMatrixPos = hips.position;
worldPosMatrixPos.y = .5f;
m_worldPosMatrix = Matrix4x4.TRS(worldPosMatrixPos, Quaternion.identity, Vector3.one);
// sensor.AddObservation(m_WalkDir.normalized);
//HIP POS REL TO MATRIX
sensor.AddObservation(hips.position - worldPosMatrixPos);
// sensor.AddObservation(m_JdController.bodyPartsDict[hips].rb.position);
// sensor.AddObservation(hips.forward);
// sensor.AddObservation(hips.up);
foreach (var bodyPart in m_JdController.bodyPartsDict.Values)
{
CollectObservationBodyPart(bodyPart, sensor);
}
}
public override void OnActionReceived(float[] vectorAction)
{
var bpDict = m_JdController.bodyPartsDict;
var i = -1;
bpDict[chest].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], vectorAction[++i]);
bpDict[spine].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], vectorAction[++i]);
bpDict[thighL].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], 0);
bpDict[thighR].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], 0);
bpDict[shinL].SetJointTargetRotation(vectorAction[++i], 0, 0);
bpDict[shinR].SetJointTargetRotation(vectorAction[++i], 0, 0);
bpDict[footR].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], vectorAction[++i]);
bpDict[footL].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], vectorAction[++i]);
bpDict[armL].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], 0);
bpDict[armR].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], 0);
bpDict[forearmL].SetJointTargetRotation(vectorAction[++i], 0, 0);
bpDict[forearmR].SetJointTargetRotation(vectorAction[++i], 0, 0);
bpDict[head].SetJointTargetRotation(vectorAction[++i], vectorAction[++i], 0);
//update joint strength settings
bpDict[chest].SetJointStrength(vectorAction[++i]);
bpDict[spine].SetJointStrength(vectorAction[++i]);
bpDict[head].SetJointStrength(vectorAction[++i]);
bpDict[thighL].SetJointStrength(vectorAction[++i]);
bpDict[shinL].SetJointStrength(vectorAction[++i]);
bpDict[footL].SetJointStrength(vectorAction[++i]);
bpDict[thighR].SetJointStrength(vectorAction[++i]);
bpDict[shinR].SetJointStrength(vectorAction[++i]);
bpDict[footR].SetJointStrength(vectorAction[++i]);
bpDict[armL].SetJointStrength(vectorAction[++i]);
bpDict[forearmL].SetJointStrength(vectorAction[++i]);
bpDict[armR].SetJointStrength(vectorAction[++i]);
bpDict[forearmR].SetJointStrength(vectorAction[++i]);
}
void FixedUpdate()
{
// Set reward for this step according to mixture of the following elements.
// a. Velocity alignment with goal direction.
// b. Rotation alignment with goal direction.
// c. Encourage head height.
// d. Discourage head movement.
m_WalkDir = target.position - m_JdController.bodyPartsDict[hips].rb.position;
AddReward(
+0.03f * Vector3.Dot(m_WalkDir.normalized, m_JdController.bodyPartsDict[hips].rb.velocity)
+ 0.01f * Vector3.Dot(m_WalkDir.normalized, hips.forward)
+ 0.02f * (head.position.y - hips.position.y)
- 0.01f * Vector3.Distance(m_JdController.bodyPartsDict[head].rb.velocity,
m_JdController.bodyPartsDict[hips].rb.velocity)
);
}
/// <summary>
/// Loop over body parts and reset them to initial conditions.
/// </summary>
public override void OnEpisodeBegin()
{
foreach (var bodyPart in m_JdController.bodyPartsDict.Values)
{
bodyPart.Reset(bodyPart);
}
if (m_WalkDir != Vector3.zero)
{
transform.rotation = Quaternion.LookRotation(m_WalkDir);
}
SetResetParameters();
}
public void SetTorsoMass()
{
m_ChestRb.mass = m_ResetParams.GetWithDefault("chest_mass", 8);
m_SpineRb.mass = m_ResetParams.GetWithDefault("spine_mass", 10);
m_HipsRb.mass = m_ResetParams.GetWithDefault("hip_mass", 15);
}
public void SetResetParameters()
{
SetTorsoMass();
}
}

12
Project/Assets/ML-Agents/Examples/Walker/Scripts/WalkerAgentDynamic.cs.meta
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8
Project/Assets/Puppo.meta
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351
config/trainer_config.yaml
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default:
trainer: ppo
batch_size: 1024
beta: 5.0e-3
buffer_size: 10240
epsilon: 0.2
hidden_units: 128
lambd: 0.95
learning_rate: 3.0e-4
learning_rate_schedule: linear
max_steps: 5.0e5
memory_size: 128
normalize: false
num_epoch: 3
num_layers: 2
time_horizon: 64
sequence_length: 64
summary_freq: 10000
use_recurrent: false
vis_encode_type: simple
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
FoodCollector:
normalize: false
beta: 5.0e-3
batch_size: 1024
buffer_size: 10240
max_steps: 2.0e6
Bouncer:
normalize: true
max_steps: 4.0e6
num_layers: 2
hidden_units: 64
PushBlock:
max_steps: 2.0e6
batch_size: 128
buffer_size: 2048
beta: 1.0e-2
hidden_units: 256
summary_freq: 60000
time_horizon: 64
num_layers: 2
SmallWallJump:
max_steps: 5e6
batch_size: 128
buffer_size: 2048
beta: 5.0e-3
hidden_units: 256
summary_freq: 20000
time_horizon: 128
num_layers: 2
normalize: false
BigWallJump:
max_steps: 2e7
batch_size: 128
buffer_size: 2048
beta: 5.0e-3
hidden_units: 256
summary_freq: 20000
time_horizon: 128
num_layers: 2
normalize: false
Pyramids:
summary_freq: 30000
time_horizon: 128
batch_size: 128
buffer_size: 2048
hidden_units: 512
num_layers: 2
beta: 1.0e-2
max_steps: 1.0e7
num_epoch: 3
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
curiosity:
strength: 0.02
gamma: 0.99
encoding_size: 256
VisualPyramids:
time_horizon: 128
batch_size: 64
buffer_size: 2024
hidden_units: 256
num_layers: 1
beta: 1.0e-2
max_steps: 1.0e7
num_epoch: 3
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.99
curiosity:
strength: 0.01
gamma: 0.99
encoding_size: 256
3DBall:
normalize: true
batch_size: 64
buffer_size: 12000
summary_freq: 12000
time_horizon: 1000
lambd: 0.99
beta: 0.001
3DBallHard:
normalize: true
batch_size: 1200
buffer_size: 12000
summary_freq: 12000
time_horizon: 1000
max_steps: 5.0e6
beta: 0.001
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
Tennis:
normalize: true
max_steps: 5.0e7
learning_rate_schedule: constant
batch_size: 1024
buffer_size: 10240
hidden_units: 256
time_horizon: 1000
self_play:
window: 10
play_against_latest_model_ratio: 0.5
save_steps: 50000
swap_steps: 50000
team_change: 100000
Soccer:
normalize: false
max_steps: 5.0e7
learning_rate_schedule: constant
batch_size: 2048
buffer_size: 20480
hidden_units: 512
time_horizon: 1000
num_layers: 2
self_play:
window: 10
play_against_latest_model_ratio: 0.5
save_steps: 50000
swap_steps: 50000
team_change: 100000
CrawlerStatic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 1e7
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
CrawlerDynamic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 3.5e6
# max_steps: 1e7
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
CrawlerBalanced:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
# max_steps: 3.5e6
max_steps: 1e8
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
WormDynamic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 3.5e6
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
WormStatic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 3.5e6
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
WalkerDynamic:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2048
buffer_size: 20480
max_steps: 2e7
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
Walker:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2048
buffer_size: 20480
max_steps: 2e7
summary_freq: 30000
num_layers: 3
hidden_units: 512
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
Reacher:
normalize: true
num_epoch: 3
time_horizon: 1000
batch_size: 2024
buffer_size: 20240
max_steps: 2e7
summary_freq: 60000
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.995
Hallway:
use_recurrent: true
sequence_length: 64
num_layers: 2
hidden_units: 128
memory_size: 128
beta: 1.0e-2
num_epoch: 3
buffer_size: 1024
batch_size: 128
max_steps: 1.0e7
summary_freq: 10000
time_horizon: 64
VisualHallway:
use_recurrent: true
sequence_length: 64
num_layers: 1
hidden_units: 128
memory_size: 128
beta: 1.0e-2
num_epoch: 3
buffer_size: 1024
batch_size: 64
max_steps: 1.0e7
summary_freq: 10000
time_horizon: 64
VisualPushBlock:
use_recurrent: true
sequence_length: 32
num_layers: 1
hidden_units: 128
memory_size: 128
beta: 1.0e-2
num_epoch: 3
buffer_size: 1024
batch_size: 64
max_steps: 3.0e6
summary_freq: 60000
time_horizon: 64
GridWorld:
batch_size: 32
normalize: false
num_layers: 1
hidden_units: 256
beta: 5.0e-3
buffer_size: 256
max_steps: 500000
summary_freq: 20000
time_horizon: 5
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.9
Basic:
batch_size: 32
normalize: false
num_layers: 1
hidden_units: 20
beta: 5.0e-3
buffer_size: 256
max_steps: 5.0e5
summary_freq: 2000
time_horizon: 3
reward_signals:
extrinsic:
strength: 1.0
gamma: 0.9

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