Unity-Technologies
Why is my test object not moving? Is MLagent not responding or any code issue in my project?
I am a beginner in MLagents in UNITY and my agent (the cube) is not moving Specific error from cmd:
(venv) C:\Users\Ricardo\My project>mlagents-learn --run-id=Test1
┐ ╖
╓╖╬│╡ ││╬╖╖
╓╖╬│││││┘ ╬│││││╬╖
╖╬│││││╬╜ ╙╬│││││╖╖ ╗╗╗
╬╬╬╬╖││╦╖ ╖╬││╗╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╜╜╜ ╟╣╣
╬╬╬╬╬╬╬╬╖│╬╖╖╓╬╪│╓╣╣╣╣╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╒╣╣╖╗╣╣╣╗ ╣╣╣ ╣╣╣╣╣╣ ╟╣╣╖ ╣╣╣
╬╬╬╬┐ ╙╬╬╬╬│╓╣╣╣╝╜ ╫╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╟╣╣╣╙ ╙╣╣╣ ╣╣╣ ╙╟╣╣╜╙ ╫╣╣ ╟╣╣
╬╬╬╬┐ ╙╬╬╣╣ ╫╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╟╣╣╬ ╣╣╣ ╣╣╣ ╟╣╣ ╣╣╣┌╣╣╜
╬╬╬╜ ╬╬╣╣ ╙╝╣╣╬ ╙╣╣╣╗╖╓╗╣╣╣╜ ╟╣╣╬ ╣╣╣ ╣╣╣ ╟╣╣╦╓ ╣╣╣╣╣
╙ ╓╦╖ ╬╬╣╣ ╓╗╗╖ ╙╝╣╣╣╣╝╜ ╘╝╝╜ ╝╝╝ ╝╝╝ ╙╣╣╣ ╟╣╣╣
╩╬╬╬╬╬╬╦╦╬╬╣╣╗╣╣╣╣╣╣╣╝ ╫╣╣╣╣
╙╬╬╬╬╬╬╬╣╣╣╣╣╣╝╜
╙╬╬╬╣╣╣╜
╙
Version information:
ml-agents: 0.29.0,
ml-agents-envs: 0.29.0,
Communicator API: 1.5.0,
PyTorch: 1.13.1+cpu
[INFO] Listening on port 5004. Start training by pressing the Play button in the Unity Editor.
Traceback (most recent call last):
File "C:\Users\Ricardo\AppData\Local\Programs\Python\Python37\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\Ricardo\AppData\Local\Programs\Python\Python37\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Users\Ricardo\My project\venv\Scripts\mlagents-learn.exe\__main__.py", line 7, in <module>
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\learn.py", line 260, in main
run_cli(parse_command_line())
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\learn.py", line 256, in run_cli
run_training(run_seed, options, num_areas)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\learn.py", line 132, in run_training
tc.start_learning(env_manager)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\trainer_controller.py", line 173, in start_learning
self._reset_env(env_manager)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents_envs\timers.py", line 305, in wrapped
return func(*args, **kwargs)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\trainer_controller.py", line 105, in _reset_env
env_manager.reset(config=new_config)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\env_manager.py", line 68, in reset
self.first_step_infos = self._reset_env(config)
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\subprocess_env_manager.py", line 446, in _reset_env
ew.previous_step = EnvironmentStep(ew.recv().payload, ew.worker_id, {}, {})
File "c:\users\ricardo\my project\venv\lib\site-packages\mlagents\trainers\subprocess_env_manager.py", line 101, in recv
raise env_exception
mlagents_envs.exception.UnityTimeOutException: The Unity environment took too long to respond. Make sure that :
The environment does not need user interaction to launch
The Agents' Behavior Parameters > Behavior Type is set to "Default"
The environment and the Python interface have compatible versions.
If you're running on a headless server without graphics support, turn off display by either passing --no-graphics option or build your Unity executable as server build.
I invoke the process using mlagents-learn --run-id=Test1 or similar
Code from the agent:
using System.Collections;
using System.Collections.Generic;
using UnityEngine;
using Unity.MLAgents;
using Unity.MLAgents.Sensors;
using Unity.MLAgents.Actuators;
public class CharacterAgent : Agent
{
[SerializeField] private Transform target;
Rigidbody rBody;
public override void Initialize()
{
rBody = GetComponent<Rigidbody>();
}
public override void OnEpisodeBegin()
{
// transform.position = new Vector3(Random.Range(-6.0f,-2.0f), Random.Range(-2.5f, 0.0f), Random.Range(-4.0f, 4.0f));
this.transform.position = new Vector3(-3.45f,1.28f,0);
target.position = new Vector3(3.55f,0.75f,0.57f);
}
public override void CollectObservations(VectorSensor sensor)
{
sensor.AddObservation((Vector3)transform.position);
sensor.AddObservation((Vector3)target.position);
}
public override void OnActionReceived(ActionBuffers actions)
{
float moveX = actions.ContinuousActions[0];
float moveZ = actions.ContinuousActions[1];
Debug.Log(moveX);
Debug.Log(moveZ);
float on_speed = 5f;
this.rBody.position += new Vector3(moveX,0,moveZ) * Time.deltaTime * on_speed;
}
public override void Heuristic(in ActionBuffers actionsOut)
{
ActionSegment<float> continousActions = actionsOut.ContinuousActions;
continousActions[0] = Input.GetAxisRaw("Horizontal");
continousActions[1] = Input.GetAxisRaw("Vertical");
}
private void OnTriggerEnter(Collider collision)
{
if(collision.TryGetComponent<MyTarget>(out MyTarget target)) {
AddReward(10f);
EndEpisode();
}
if (collision.TryGetComponent<MyWalls>(out MyWalls walls))
{
AddReward(-2f);
EndEpisode();
}
}
}
Code of the goal (sphere):
using System.Collections;
using System.Collections.Generic;
using UnityEngine;
public class MyTarget : MonoBehaviour
{
}
Code of the walls:
using System.Collections;
using System.Collections.Generic;
using UnityEngine;
public class MyWalls : MonoBehaviour
{
}
Unity logs when I debug:
[Adaptive Performance] No Provider was configured for use. Make sure you added at least one Provider in the Adaptive Performance Settings.
UnityEngine.AdaptivePerformance.AdaptivePerformanceInitializer:Initialize () (at ./Library/PackageCache/[email protected]/Runtime/Core/AdaptivePerformanceInit.cs:60)
Couldn't connect to trainer on port 5004 using API version 1.5.0. Will perform inference instead.
UnityEngine.Debug:Log (object)
Unity.MLAgents.Academy:InitializeEnvironment () (at ./Library/PackageCache/[email protected]/Runtime/Academy.cs:459)
Unity.MLAgents.Academy:LazyInitialize () (at ./Library/PackageCache/[email protected]/Runtime/Academy.cs:279)
Unity.MLAgents.Academy:.ctor () (at ./Library/PackageCache/[email protected]/Runtime/Academy.cs:248)
Unity.MLAgents.Academy/<>c:<.cctor>b__83_0 () (at ./Library/PackageCache/[email protected]/Runtime/Academy.cs:117)
System.Lazy`1<Unity.MLAgents.Academy>:get_Value ()
Unity.MLAgents.Academy:get_Instance () (at ./Library/PackageCache/[email protected]/Runtime/Academy.cs:132)
Unity.MLAgents.Agent:LazyInitialize () (at ./Library/PackageCache/[email protected]/Runtime/Agent.cs:451)
Unity.MLAgents.Agent:OnEnable () (at ./Library/PackageCache/[email protected]/Runtime/Agent.cs:365)
I do, I found some solutions but still not working, and the same error appears... is that a version issue from python/torch?
I do, I found some solutions but still not working, and the same error appears... is that a version issue from python/torch?
I saw your behavior type is Heuristic. Change your behavior type to default if you want it controlled by python
I do, I found some solutions but still not working, and the same error appears... is that a version issue from python/torch?
I saw your behavior type is Heuristic. Change your behavior type to default if you want it controlled by python
I see, then I will re-do the project and update it to default... because I've made a lot of changes looking up in some tutorials and how-to-solve guides with similar issues to prevent any config conflict with this
This issue is stale because it has been open for 30 days with no activity.
![github-actions[bot] avatar](https://avatars.githubusercontent.com/in/15368?v=4 "Published by a pub.dev verified publisher"){kind=small}
This issue was closed because it has been inactive for 14 days since being marked as stale. Please open a new issue for related bugs.