Off Policy Meta-Reinforcement Learning

Summary

  • Our team explored off-policy algorithms for meta-reinforcement learning, benchmarking them on meta-world
  • The two main approaches were based on used latent context variables or off-policy MAML style gradient updates
  • Developed code to emprically test these approaches using rlkit, with results and observations being outlined in the report

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