Training a Reinforcement Learning agent to solve Frozen Lake game from OpenAI gym.
This is my project for the Reinforcement Learning class taken as an elective for the Master's in Data Science program at the University of San Francisco.
The goal is to train an agent to get to the goal from the start without falling into a hole on a frozen lake. The lake is extremely slippery, so you don't always go in the direction you indented to, which adds to the complexity of the problem.
I used a Q-learning as well as DQN reinforcement learning algorithms to train my agent.
