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

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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

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

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