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A simple Q-learning implementation in OpenAI Gym's "Taxi-v3" environment.

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Taxi-v3 Q-Learning

A simple Q-learning implementation in OpenAI Gym's "Taxi-v3" environment.

What is OpenAI Gym?

OpenAI Gym is a toolkit for developing and comparing reinforcement algorithms. It provides a wide range of environments with different reinforcement learning tasks.

It can be found on GitHub here and documentation is here.

Setup & Running the code.

Python 3 is required and can be downloaded here.

Installing required libraries.

pip3 install -r requirements.txt

Running the agent.

py agent.py

Possible Improvements

  • Command line arguments to modify the amount of training episodes.
  • Saving and loading the q-table.
  • Tuning alpha, gamma and epsilon by decaying over training episodes.

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A simple Q-learning implementation in OpenAI Gym's "Taxi-v3" environment.

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