Hello Akash, thanks for getting in touch, glad you like the project idea.
Getting familiar with the codebase especially src/mlpack/methods/reinforcement_learning/ should be the first step, as you already pointed out. Running the tests: (rl_components_test.cpp) 'bin/mlpack_test -t RLComponentsTest' and (q_learning_test.cpp) 'bin/mlpack_test -t QLearningTest' should help to understand the overall structure. Also you might find Shangtong's blog posts helpful: http://www.mlpack.org/gsocblog/ShangtongZhangPage.html If you like you can work on a simple RL method like (stochastic) Policy Gradients and use that to jump into the codebase, but don't feel obligated. > I am thinking of working on my application at the earliest this week. Is that > ok > ? I am going through the code base and as I find something to talk about/on, > can > I trouble you people with my questions? There might be a lot, some even > stupid ! Sounds like a good plan, let us know if we should clarify anything we are here to help. Thanks, Marcus > On 13. Feb 2018, at 19:08, Akash Shivram <[email protected]> wrote: > > Hey there! > Congratulations on getting into GSoC' 18!! > > I was going through the organisations participating this year searching for > organisations working in ML and DL related field. I came across mlpack and > was delighted to see a project on RL!! I like RL and and wanted some project > to do in this field. > I have experience working with Neural Networks, Reinforcement Leaning, and > Deep Q Learning. As this is the first day of me with your repository, > I have gone through requirements for an applicant for 'Reinforcement > Learning' project and trying to go through as many papers listed as possible. > Are there any more 'bonus' papers, or anything extra that wold be required. > Moreover, I am thinking of working on my application at the earliest this > week. Is that ok ? I am going through the code base and as I find something > to talk about/on, can I trouble you people with my questions? There might be > a lot, some even stupid ! > > Thank you > > PS : This mail went too long!! Sorry for the long read ! > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
