update

docker/README.md

@@ -7,7 +7,7 @@ _tl;dr [dockerhub url](https://hub.docker.com/r/justheuristic/practical_rl/)_
 We recommend you to use either native docker (recommended for linux) or kitematic(recommended for windows).
 * Installing [kitematic](https://kitematic.com/), a simple interface to docker (all platforms)
 * Pure docker: Guide for [windows](https://docs.docker.com/docker-for-windows/), [linux](https://docs.docker.com/engine/installation/), or [macOS](https://docs.docker.com/docker-for-mac/).
-* If you want to use your GPU make sure you have [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) and [NVidia driver](https://www.nvidia.com/en-us/drivers/unix/) + [CUDA 10.2](https://developer.nvidia.com/cuda-downloads) installed
+* If you want to use your GPU make sure you have [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) and [NVidia driver](https://www.nvidia.com/en-us/drivers/unix/) + [CUDA 10.2](https://developer.nvidia.com/cuda-downloads) installed
 
 Below are the instructions for both approaches.
 

setup_colab.sh

@@ -6,7 +6,7 @@ wget -q https://raw.githubusercontent.com/yandexdataschool/Practical_RL/master/x
 
 # Download & import Atari ROMs (Colab stopped bundling them around the beginning of June 2021)
 
-gdown -q https://drive.google.com/uc?id=1dCLEJcJGDDV4l5ssoexP2TEOVuBfyh7D
+gdown -q https://drive.google.com/uc?id=1c6_W2Fig92hm5FRIc2Mpc_ZZyr6o52lF
 
 # Alternative download:
 # wget -q http://www.atarimania.com/roms/Roms.rar

week01_intro/README.md

@@ -11,7 +11,7 @@
 
 
 ## More materials:
-* __[recommended]__ - awesome openai post about evolution strategies - [blog post](https://blog.openai.com/evolution-strategies/), [article](https://arxiv.org/abs/1703.03864)
+* __[recommended]__ - awesome openai post about evolution strategies - [blog post](https://openai.com/research/evolution-strategies), [article](https://arxiv.org/abs/1703.03864)
 * __[recommended]__ - formal explanation of crossentropy method in [general](https://people.smp.uq.edu.au/DirkKroese/ps/CEEncycl.pdf) and for [optimization](https://people.smp.uq.edu.au/DirkKroese/ps/CEopt.pdf)
 * Deep learning course (if you want to learn in parallel) - https://github.com/yandexdataschool/HSE_deeplearning
 * Video on genetic algorithms (english) - [video](https://www.youtube.com/watch?v=ejxfTy4lI6I)
@@ -23,10 +23,10 @@
 
 
 ## Practice assignment
-Instant dive in: [__seminar_gym_interface__](https://colab.research.google.com/github/yandexdataschool/Practical_RL/blob/master/week01_intro/seminar_gym_interface.ipynb), [__crossentropy_method__](https://colab.research.google.com/github/yandexdataschool/Practical_RL/blob/master/week01_intro/crossentropy_method.ipynb),
+Instant dive in: [__seminar_gymnasium_interface__](https://colab.research.google.com/github/yandexdataschool/Practical_RL/blob/master/week01_intro/seminar_gymnasium_interface.ipynb), [__crossentropy_method__](https://colab.research.google.com/github/yandexdataschool/Practical_RL/blob/master/week01_intro/crossentropy_method.ipynb),
 [__deep_crossentropy_method__](https://colab.research.google.com/github/yandexdataschool/Practical_RL/blob/master/week01_intro/deep_crossentropy_method.ipynb)
 
-* Open `gym_interface.ipynb` and follow instructions from there
+* Open `seminar_gymnasium_interface.ipynb` and follow instructions from there
 * After you're done there, proceed to `crossentropy_method.ipynb`
 * You can find homework and bonus assignment descriptions at the end of that notebook.
-* Note: so far it's enough to say `pip install gym` on top of any data-science-stuffed python, but we'd appreciate if you gradually switch to [full installation](https://github.com/openai/gym#installing-everything).
+* Note: so far it's enough to say `pip install gymnasium` on top of any data-science-stuffed python, but we'd appreciate if you gradually switch to [full installation](https://github.com/Farama-Foundation/Gymnasium).