How to  train our first Reinforcement Learning agent! | Reinforcement Learning Part-3
Channel: CampusX
Date: 2022-07-12

Looking only at the theoretical portions of Reinforcement Learning, people often get bored. To spice things up, we apply the theory into practice and apply SARSA and Q-Learning to the Cliff Walking Problem. We use a library called OpenAI Gym to spare the time of coding an RL Environment ourselves. Some interesting things were noticed about these algorithms when we compared them. Happy Learning!

OpenAI Gym : https://www.gymlibrary.ml/
Gym Github : https://github.com/openai/gym
PyCharm : https://www.jetbrains.com/pycharm/download/#section=windows

Project Github Link: https://github.com/rajtilakls2510/reinforcement_learning/tree/part_3

Reinforcement Learning Book by Sutton and Barto: http://incompleteideas.net/book/the-book.html
Free Reinforcement Learning Course from IIT Madras: https://nptel.ac.in/courses/106106143

Music: bensound.com

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⌚Time Stamps⌚

0:00 - Intro
0:41 - Cliff Walking Problem
2:15 - Gym Interface
4:04 - Gym Cliff Walking Env
5:28 - Setup
7:36 - Coding a Random Agent
15:49 - Coding a SARSA Agent
27:09 - Seeing how the agent performs
33:02 - Coding a Q-Learning Agent
39:58 - Comparing SARSA and Q-Learning
41:11 - Outro