Off-Dynamics Reinforcement Learning


  • Tackled the problem of domain transfer in reinforcement learning with a novel approach that shapes the reward function of the source domain
  • The method learns auxiallry classifiers with little modification to RL algorithm instead of explicitly modeling dynamics
  • Developed code for empirical benchmarking of the method on robotics tasks with simulators like MuJoCo and PyBullet