Josemvg / frozen-lake

Short experiment on Reinforcement Learning with the Frozen-Lake gymnasium environment

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Frozen Lake

Hi! This is a short experiment on Reinforcement learning using the OpenAI gymnasium library. We're going to train an agent to find the shortest path to the goal in the Frozen Lake game using Q-learning. This project was completed as part of the Machine Learning II course for the Big Data Master's Degree program at Comillas ICAI University.

Our team of contributors includes:

Name Email
Jorge Ayuso Martínez jorgeayusomartinez@alu.comillas.edu
Carlota Monedero Herranz carlotamoh@alu.comillas.edu
José Manuel Vega Gradit josemanuel.vega@alu.comillas.edu

We've created a short animated gif showing the training process of our agent on evaluation:

train_gif

And here's another one that showcases its performance on 100 evaluations:

eval_gif

If you want to check out our code and reproduce our results, head over to our GitHub repo: https://github.com/carlota-moh/frozen-lake

About

Short experiment on Reinforcement Learning with the Frozen-Lake gymnasium environment


Languages

Language:Jupyter Notebook 96.5%Language:Python 3.5%