Train AI to Beat Super Mario Bros! || Reinforcement Learning Completely from Scratch

Today we'll be implementing a Reinforcement Learning algorithm named the Double Deep Q Network algorithm. A lot of other videos will use a library like Stable Baselines, however, today we'll be building this completely from scratch. It'll be used to train the computer to play Super Mario Bros on the NES! This is a tutorial aimed at people that have a base level understanding of ML, but not necessarily reinforcement learning. Also, it's perfect if you're looking for a personal project to add to your resume that can be completed in a weekend. Additionally, if you don't have the resources to train this locally, I highly recommend checking out Google Colab Notebooks! This is my first ever YouTube video and I've been really excited to share this with you guys! If there are any questions or if anyone has any tips/advice, please don't hesitate to comment down below! 00:00 Demo & Intro 03:02 Key Reinforcement Learning Vocabulary 07:47 Epsilon-Greedy Approach 09:32 Replay Buffer 10:20 Action-Value Function Intuition 15:19 The DDQN Algorithm 18:39 DDQN Pseudocode 19:39 Implementation in Code 30:21 The AI Beats the Level! 30:56 Conclusion SOURCE CODE https://github.com/Sourish07/Super-Ma... PAPERS USED AS REFERENCE Human-level control through deep reinforcement learning https://www.nature.com/articles/natur... Deep Reinforcement Learning with Double Q-learning https://arxiv.org/pdf/1509.06461.pdf DOCUMENTATION PyTorch Documentation https://pytorch.org/tutorials/interme... https://pytorch.org/rl/reference/data... Gymnasium Documentation https://gymnasium.farama.org/index.html https://gymnasium.farama.org/api/wrap... TEXTBOOKS Learning Deep Learning by Magnus Ekman https://www.nvidia.com/en-us/training... Reinforcement Learning, Second Edition by Sutton, Barto https://mitpress.mit.edu/978026203924... OTHER CNN Explainer https://poloclub.github.io/cnn-explai... Introducing ChatGPT https://openai.com/blog/chatgpt All content on this channel is produced by and is the intellectual property of Sourish Kundu LLC.