Reinforcement Learning Course

Reinforcement Learning Course#

An introduction to reinforcement learning. Proficieny in python is required.

This course will introduce the fundamentals of Reinforcement learning (RL) and Deep learning techniques. The course will cover the Tabular solution methods, such as the finite Markov Decision Processes and Temporal-Difference learning. It will also cover approximation solution methods, as on-policy and off-policy approximations. By the end of the course, new deep-learning techniques will be introduced.

Professors#

Dr. Jean-Alexis Delamer

Class time#

  • Tue: 12:30pm - 1:20pm (MULH 4024)

  • Thu: 11:30am - 12:20pm (MULH 4024)

  • Fri: 1:30pm - 2:20pm (MULH 4024)

Office hours#

  • Tue: 10:30am - 11:30am (Annex 9C)

  • Thu: 10:00am - 11:00am (Annex 9C)

  • Fri: 9:00am - 10:00am (Annex 9C)

Contents