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remove nvidia driver and cuda toolkit



Ubuntu

To remove CUDA Toolkit: 
$ sudo apt-get --purge remove "*cublas*" "cuda*"
To remove NVIDIA Drivers: 
$ sudo apt-get --purge remove "*nvidia*"




remove following in .bashrc


export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}











































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   迴力球遊戲－ATARI     賽車遊戲DQN－ATARI 賽車遊戲－TORCS Ref:      李宏毅老師 YOUTUBE DRL 1-3   On-policy VS Off-policy   On-policy      The agent learned and the agent interacting with the environment is the same      阿光自已下棋學習  Off-policy      The agent learned and the agent interacting with the environment is different       佐助下棋，阿光在旁邊看         Add a baseline:       It is possible that R is always positive       So R subtract a expectation value       Policy in " Policy  Gradient" means output action, like left/right/fire        gamma-discounted rewards:   時間愈遠的貢獻，降低其權重      Reward Function & Action is defined in prior to training      MC v.s. TD    MC 蒙弟卡羅: critic after episode end  : larger variance(cuz conditions differ a lot in every episode), unbiased (judge until episode end, more fair)    TD: Temporal-difference approach: critic during episode :smaller variance, biased maybe           atari : a3c  ...




















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DeepRacer




























Preliminary training:      deepracer-github-simapp.tar.gz   Reward function:  ./opt/install/sagemaker_rl_agent/lib/python3.5/site-packages/markov/environments/deepracer_env.py     action = [steering_angle, throttle]  TRAINING_IMAGE_SIZE = (160, 120)                 Plotted waypoints in vertices array of hard track      Parameters:  on_track,  x, y,  distance_from_center, car_orientation, progress, steps,                                                                           throttle, steering,  track_width,  waypoints, closest_waypoints        Note: Above picture is from https://yanpanlau.github.io/2016/10/11/Torcs-Keras.html




















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Frameworks overview




























   Picture courtesy from Paul Huang  




















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