Adversarial Reinforcement Learning is a year-long project taken up by a group of members at IEEE-NITK. As a part of this project we aim to explore Adversarial Attacks in Reinforcement Learning, and look for possible defenses. The code for this project can be found in this repository. The video presentation can be found here and virtual-expo here.

Team Members:

  • Madhuparna Bhowmik
  • Akash Nair
  • Saurabh Agarwala
  • Videh Raj Nema
  • Kinshuk Kashyap
  • Manav Singhal