TECHNICAL WORKSHOP SERIES - A Python Example of Q-learning (1st Offering) by: Xiaofeng Liu (Michael)

Thursday, June 13, 2024 - 10:00

Technical Workshop Series

A Python Example of Q-learning (1st Offering)


Presenter:  Xiaofeng Liu (Michael)

Date:  Thursday, June 13th, 2024

Time:  10:00 AM

Location: 4th Floor (Lecture Space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)


This is a hands-on workshop; it is recommended that you bring your laptop.



Reinforcement learning (RL) is training machine learning models to make a sequence of decisions. Q-learning is a type of RL with a model-free environment which achieves learning by interaction with the environment instead of transition probabilities. This workshop will give a Python example of how to use Q-learning to solve a shortest-path problem.


Workshop Outline:

  • To review the principle of RL and Q-learning
  • To define the environment
  • To implement Q-learning with Jupyter notebook



Principle of RL, Foundation of Q-learning, Python, Jupyter notebook



Xiaofeng is a PhD Candidate in Computer Science. His research interests mainly focus on Congestion Control for V2V communication in VANET (Vehicular Ad hoc Network).


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