nalexus / reinforcement-learning-ucu

Link to my ML course summary on DQN paper, i.e. ”Playing Atari with Deep Reinforcement Learning” by Mnih et al.:

https://drive.google.com/file/d/1EFoSBxw5Bg1PC6OYREQbgzw8m7HW30a1/view?usp=sharing

Link to 2021 year (most recent NeurIPS not included) literature review for diploma on topic ”Exploration of Reinforcement Learning agent in procedurally-generated environments with sparse rewards”:

https://drive.google.com/file/d/1E1m-8x0WHPM0F78JmhMuJiMyslJjTo9C/view?usp=sharing

Reinforcement-Learning-course-UCU (Presentations and HW)

Presentation on paper "Continuous control ith deep reinforcement learning" by Lillicrap et al. (2016): https://docs.google.com/presentation/d/1RhxpTfulqt0lxIYbxe-krUrkT81h5WWE-prEgkUSepE/edit?usp=sharing

Presentation on paper "Curiosity-driven Exploration by Self-supervised Prediction" by Pathak et al. (2017) https://docs.google.com/presentation/d/1SZOhFrjSOmuP93aRsowYLkZlTPFzXp3WIxzLTk0xHVY/edit?usp=sharing

HW1 - Fundamentals (Value Iteration etc.): https://colab.research.google.com/drive/1WPW49MCFbr30Aqoi0oTbNSbOt6EXjZHj?usp=sharing

HW2 - DQN: https://colab.research.google.com/drive/1wan_6Wslbg771KIVe3oxX9HsqQbaTtK6?usp=sharing

HW3 - Policy Gradients: https://colab.research.google.com/drive/1-yQMbO_f-sMTChZF1bncpv3V8UXJ6P33?usp=sharing

HW4 - DDPG: https://colab.research.google.com/drive/1y16VBXA2u0Tehhx7FV1SJGB4pRWHQZZy?usp=sharing

HW5 - PPO: https://colab.research.google.com/drive/10Xj6Vg7xet3qabkCqijBfrN_WhDNlcjo?usp=sharing

HW6 - Exploration strategies: https://colab.research.google.com/drive/1U_Mxbv-EJnvnvf54XDRNDne3g3Hk7f3E?authuser=1#scrollTo=-Oanmp9SoU6v

HW7 - MCTS: https://colab.research.google.com/drive/191O385zwdXwIS8Lh-pYIewrfE0tDbhWl?usp=sharing