A Reinforcement Learning Approach for Locomotion





Abstract


  • This project is the term project for UCLA CS275 18Winter. We explored the Reinforcement Learning approach for locomotion training. We implemented the Evolution Strategy and A3C algorithm on the BipedalWalker-v2 physical environment provided by OpenAI Gym. Both led to good results with satisfying accumulated rewards.
  • Comparing the two solutions, we decided that A3C algorithm is stabler and more suited for this problem. Then we conducted further experiments on the advanced BipedalWalkerHardcore-v2 environment that has randomly generated terrain obstacles, which achieved relatively modest performance. We also explored deeper into the underlying explanation for the experiment results.