[mlpack] Regarding Proposal for Reinforcement Learning

[Amit Panghal]

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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