Ml-Agentsのエラーについて

前提・実現したいこと

UnityのMl-agentsを用い強化学習及び、模倣学習をしたい

発生している問題・エラーメッセージ

Ml-agentsの最新バージョンである 0.11.0を使用しているが参考文献が少なすぎて解決できない。

(base) C:\Users\user\Documents\ml-agents-master\ml-agents>mlagents-learn ../config/trainer_config.yaml --run-id=firstRun --train
2019-11-14 14:45:59.431992: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_100.dll'; dlerror: cudart64_100.dll not found
2019-11-14 14:45:59.436532: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.



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INFO:mlagents.trainers:CommandLineOptions(debug=False, num_runs=1, seed=-1, env_path=None, run_id='firstRun', load_model=False, train_model=True, save_freq=50000, keep_checkpoints=5, base_port=5005, num_envs=1, curriculum_folder=None, lesson=0, slow=False, no_graphics=False, multi_gpu=False, trainer_config_path='../config/trainer_config.yaml', sampler_file_path=None, docker_target_name=None, env_args=None, cpu=False)
INFO:mlagents.envs:Start training by pressing the Play button in the Unity Editor.

該当のソースコード

上記のメッセージが出たのちUnity上でplayを押すと以下のメッセージが出る。

Process Process-1:
Traceback (most recent call last):
  File "c:\users\user\anaconda3\lib\multiprocessing\process.py", line 297, in _bootstrap
    self.run()
  File "c:\users\user\anaconda3\lib\multiprocessing\process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\subprocess_env_manager.py", line 82, in worker
    env = env_factory(worker_id)
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\trainers\learn.py", line 359, in create_unity_environment
    args=env_args,
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\environment.py", line 105, in __init__
    aca_output = self.send_academy_parameters(rl_init_parameters_in)
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\environment.py", line 689, in send_academy_parameters
    return self.communicator.initialize(inputs)
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\rpc_communicator.py", line 88, in initialize
    "The Unity environment took too long to respond. Make sure that :\n"
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 are linked to the appropriate Brains
         The environment and the Python interface have compatible versions.
Traceback (most recent call last):
  File "c:\users\user\anaconda3\lib\multiprocessing\connection.py", line 312, in _recv_bytes
    nread, err = ov.GetOverlappedResult(True)
BrokenPipeError: [WinError 109] パイプは終了しました。

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\subprocess_env_manager.py", line 59, in recv
    response: EnvironmentResponse = self.conn.recv()
  File "c:\users\user\anaconda3\lib\multiprocessing\connection.py", line 250, in recv
    buf = self._recv_bytes()
  File "c:\users\user\anaconda3\lib\multiprocessing\connection.py", line 321, in _recv_bytes
    raise EOFError
EOFError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\users\user\anaconda3\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "c:\users\user\anaconda3\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Users\user\Anaconda3\Scripts\mlagents-learn.exe\__main__.py", line 9, in <module>
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\trainers\learn.py", line 408, in main
    run_training(0, run_seed, options, Queue())
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\trainers\learn.py", line 222, in run_training
    options.sampler_file_path, env.reset_parameters, run_seed
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\subprocess_env_manager.py", line 225, in reset_parameters
    return self.env_workers[0].recv().payload
  File "c:\users\user\anaconda3\lib\site-packages\mlagents\envs\subprocess_env_manager.py", line 62, in recv
    raise UnityCommunicationException("UnityEnvironment worker: recv failed.")
mlagents.envs.exception.UnityCommunicationException: UnityEnvironment worker: recv failed.