Unity Timeout Exception when using Heuristic Only

Unity Engine
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1

I am trying to train an imitation learning agent. I have entered the Heuristic function in my AI so I can control it. But if I select ‘Heuristic Only’ as behaviour type, the environment crashes after about 50 seconds saying Unity Timeout Exception. Full error message is below. I have Python 3.8.5, Unity 2020.3.0f1. I have tried a different Neural Net. Behaviour Type ‘Default’ works as expected but I can’t train my agent that way. Anyone know how I could get it working again? Thanks.

Also, I’m using Anaconda3 for the virtual environment. A demo file is still created at the end of the run.

(mlagents-r8) E:\Programming\Unity Hub\My projects\Rocket Ball wAI>mlagents-lear
n --time-scale 0.002 --target-frame-rate 60 --run-id P2AIAtt5

(Unity logo)

Version information:
  ml-agents: 0.25.0,
  ml-agents-envs: 0.25.0,
  Communicator API: 1.5.0,
  PyTorch: 1.8.0
2021-03-25 22:56:04 INFO [learn.py:245] run_seed set to 7283
2021-03-25 22:56:04 INFO [torch.py:58] default Torch device: cuda
2021-03-25 22:56:06 INFO [environment.py:210] Listening on port 5004. Start trai
ning by pressing the Play button in the Unity Editor.
2021-03-25 22:56:12 INFO [environment.py:112] Connected to Unity environment wit
h package version 1.9.0-preview and communication version 1.5.0
2021-03-25 22:57:18 INFO [subprocess_env_manager.py:220] UnityEnvironment worker
0: environment stopping.
2021-03-25 22:57:18 INFO [trainer_controller.py:81] Saved Model
Traceback (most recent call last):
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\runpy.py", line 194, in _r
un_module_as_main
    return _run_code(code, main_globals, None,
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\runpy.py", line 87, in _ru
n_code
    exec(code, run_globals)
  File "E:\Programming\Anaconda3\envs\mlagents-r8\Scripts\mlagents-learn.exe\__m
ain__.py", line 7, in <module>
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\learn.py", line 250, in main
    run_cli(parse_command_line())
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\learn.py", line 246, in run_cli
    run_training(run_seed, options)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\learn.py", line 125, in run_training
    tc.start_learning(env_manager)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents_env
s\timers.py", line 305, in wrapped
    return func(*args, **kwargs)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\trainer_controller.py", line 173, in start_learning
    self._reset_env(env_manager)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents_env
s\timers.py", line 305, in wrapped
    return func(*args, **kwargs)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\trainer_controller.py", line 105, in _reset_env
    env_manager.reset(config=new_config)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\env_manager.py", line 68, in reset
    self.first_step_infos = self._reset_env(config)
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\subprocess_env_manager.py", line 333, in _reset_env
    ew.previous_step = EnvironmentStep(ew.recv().payload, ew.worker_id, {}, {})
  File "e:\programming\anaconda3\envs\mlagents-r8\lib\site-packages\mlagents\tra
iners\subprocess_env_manager.py", line 98, in recv
    raise env_exception
mlagents_envs.exception.UnityTimeOutException: The Unity environment took too lo
ng 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.
2

Ok, so you don’t connect to the port when you’re training an imitation learning agent, you just record the demo file. Egg is on my face.