nov05 / 20240223_udacity_drlnd_p2_env.md

Last active November 18, 2024 21:20

Udacity Deep Reinforcement Learning - p2 & `deeprl` env setup

👉 check the drlnd_py310 env setup notes
👉 check the p1 env setup notes
👉 course curriculum
👉 Colab notebooks

nov05 / 20240222_issue gym.wrappers.Monitor.md

Last active February 22, 2024 17:03

⚠️ issue: from gym.wrappers import Monitor caused ImportError: cannot import name 'Monitor' from 'gym.wrappers'.

solution (2022'):

from gym.wrappers.record_video import RecordVideo
env = gym.make('CartPole-v1', render_mode="rgb_array")
env = RecordVideo(env, './video',  episode_trigger = lambda episode_number: True)
env.reset()

nov05 / 20240219_reinforcement learning_pong PPO training log 1200e.md

Last active February 19, 2024 10:31

20240218_pong-PPO.ipynb
👉 training log for reference
1000 episodes, T4 GPU, Wall time: 1h 38min 14s

Episode: 20, score: -15.750000
[-16. -16. -16. -16. -16. -16. -16. -14.]
Episode: 40, score: -12.625000

nov05 / 20240218_reinforcement learning_pong training log 1200e.md

Created February 19, 2024 06:00

20240218_reinforcement learning_pong training log 1200e

20240217_pong_REINFORCE.ipynb
👉 training log for reference
1200 episodes on T4 GPU, Wall time: 2h 12min 12s

Episode: 20, score: -14.500000
[-14. -15. -16. -13. -14. -16. -16. -12.]
Episode: 40, score: -14.500000

nov05 / 20240218_reinforcement learning_pong training log for reference.md

Last active February 19, 2024 04:05

20240218_reinforcement learning_pong training log for reference

20240217_pong_REINFORCE.ipynb
👉 training log for reference
800 episodes on T4 GPU, Wall time: 1h 17min 44s

Episode: 20, score: -14.000000
[-15. -17. -15. -14. -13. -13. -16.  -9.]

nov05 / 20240218_python_PyWhatKit_issue_313.md

Created February 19, 2024 00:21

20240218 python PyWhatKit issue 313

Ankit404butfound/PyWhatKit#313

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/usr/local/lib/python3.10/dist-packages/Xlib/support/unix_connect.py in get_socket(dname, host, dno)
     75             s = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
---> 76             s.connect('/tmp/.X11-unix/X%d' % dno)
     77     except OSError as val:

nov05 / 20240215_udacity reinforcement learning_DQN project submission.md

Last active February 15, 2024 17:32

👉 Unity ML-Agents `Banana Collectors` Project Submission

For this toy game, two Deep Q-network methods are tried out. Since the observations (states) are simple (not in pixels), convolutional layers are not in use. And the evaluation results confirm that linear layers are sufficient for solving the problem.
- Double DQN, with 3 linear layers (hidden dims: 256*64, later tried with 64*64)
- Dueling DQN, with 2 linear layers + 2 split linear layers (hidden dims: 64*64)

▪️ The Dueling DQN architecture is displayed as below.

nov05 / 20240211_stream unity alagents from colab to twitch.md

Last active February 12, 2024 03:23

20240211 【error】stream unity alagents from colab to twitch

go to the cell in the notebook
pip install the latest mlagents version. using banana.ymal in the new format.

⚠️ error

mlagents_envs.exception.UnityEnvironmentException: Environment shut down with return code -6 (SIGABRT).

nov05 / 20240211_stream unity mlagents from colab to twitch.md

Last active February 12, 2024 03:27

20240211 stream unity mlagents display from google colab to twitch

👉 check the colab notebook
👉 go to the cell

⚠️ issue

mono_gdb_render_native_backtraces not supported on this platform, unable to find gdb or lldb

installed mlagents release 1. used trainer_config.yaml in the old format.

nov05 / 20240211_udacity_drlnd_mlagents.md

Last active February 25, 2024 11:52

20240211_udacity reinforcement learning unity mlagents env setup

Udacity Deep Reinforcement Learning - p1 env setup

👉 for the course projcts, Unity MLAgents - Banana Collector, etc.
👉 go to the Banana and VisualBanana notebooks
👉 go to the course repo
👉 check course curriculum

Window 11, VSCode, Minicoda, Powershell

nov05

Udacity Deep Reinforcement Learning - p2 & deeprl env setup

👉 Unity ML-Agents Banana Collectors Project Submission

Udacity Deep Reinforcement Learning - p1 env setup

Udacity Deep Reinforcement Learning - p2 & `deeprl` env setup

👉 Unity ML-Agents `Banana Collectors` Project Submission