## Materials:
* [__Lecture slides__](https://yadi.sk/i/-EUHXUXOTC5t9Q)
* __Russian:__
  * Intro to RL - [video](https://yadi.sk/i/HpRw6zYv3SPmFf)
  * Seminar - [video](https://yadi.sk/i/gRTVCHfM3SPmHo)

* __English:__
  * [__main__] Video-intro by David Silver (english) - [video](https://www.youtube.com/watch?v=2pWv7GOvuf0)
  * [__main__] Lecture by J Schulman with crossentropy method explained (english) - [url](https://www.youtube.com/watch?v=aUrX-rP_ss4&list=PLCTc_C7itk-GaAMxmlChrkPnGKtjz8hv1)
  * Optional lecture by David Silver (english) - [video](https://www.youtube.com/watch?v=lfHX2hHRMVQ)


## More materials:
* __[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)
* Another guide to genetic algorithm (english) - [video](https://www.youtube.com/watch?v=zwYV11a__HQ)
* About Differential evolution (english) - [pdf](http://jvanderw.une.edu.au/DE_1.pdf)
* Video on Ant Colony Algorithm (english) - [video](https://www.youtube.com/watch?v=D58nLNLkb0I)
* Longer video on Ant Colony Algorithm (english) - [video](https://www.youtube.com/watch?v=xpyKmjJuqhk)
* Longer video on corssentropy method (russian) - [video](https://yadi.sk/i/5yf_4oGI3EDJhJ)
  

## Practice assignment
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 `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 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).
