RL_HW3

Repository for the third homework for the Reinforcement Learning course of the M.Sc in Artificial Intelligence and Robotics at Sapienza University.

Topics

• Deep Reinforcement Learning
• A2C
• DDQN+PER

Content

• document.pdf, file where are listed the tasks to perform.
• Theory.pdf, file containing the responses to the theory's question and the explanation of the code.
• assignment3/car_racing folder, that contains the code files:
  • student.py python file that contains my implementation of the DDQN policy agent for the CarRacing-v2 gym environment.
  • main.py given file used to manage the train/evalutation of the agent.
  • auxiliary.py python file in which I implemented both the ReplayBuffer with prioritized experience and the Network class used to define the DDQN networks.
  • a2c.py stand alone file for the implementation of the A2C policy agent for the CarRacing-v2 gym environment.