Second-Order Methods for Policy Search in Reinforcement Learning

Summary

  • Wrote thesis work aimed at improving the convergence rate and theoretical guarantees of policy search methods
  • Evaluated second-order methods like Newton method and approximations motivated by natural gradient information
  • Empirically compared algorithms using exact Hessian and its approximations motivated by Fisher information

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