Hi Mentors, I am 1st year graduate student in computer science at New York University. I had spent significant amount of time going through RL papers to draft a proposal for RL algorithm to play Atari games. I have a rough understanding of code structure in ml-pack. I have a draft proposal ready for implementing double DQN. I am bit confused regarding, do I need to implement the agent which using gym api's to interact with environment and uses the current framework( https://github.com/mlpack/mlpack/blob/master/src/mlpack/methods/reinforcement_learning/q_learning.hpp) Or implement double dqn , PPO algorithms , Persistent Advantage Learning DQN. Isnt double DQN and DQN, already implemented?
regards, Amit Panghal, Courant Insitiute of Mathematical Sciences, New York University
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