[mlpack] Greetings GSOC 19 : Idea Reinforcement Learning

[Rohan Raj]

Dear Ryan and Marcus,

Please answer my doubts sent in my previous mail as soon as you get time.

Thanks,

Rohan Raj
Indian Institute of Technology Guwahati
Assam , India
Phone : +91 8723990557



On Wed, 27 Mar 2019 at 10:10, Rohan Raj <rajrohan1108 at gmail.com> wrote:

> Hello all,
>
> Apologies for the delay in reply. I have started writing the proposal for
> the coming GSOC year. I sincerely wanted to know a few things from the
> authors. For the PPO Reinforcement Learning algorithm, we can either have 2
> different neural networks for policy and value estimation or club these
> into a single model with different outputs (as openai baselines or
> deepmind). The first option is approachable in MlPack. However, I am
> confused with the second approach. I feel that the following lines (
> https://github.com/mlpack/mlpack/blob/2635297c8793396e57469bc731451fbe18bed656/src/mlpack/methods/ann/layer/add_merge.hpp#L127-L128)
> might be helpful for the purpose, however, I am not completely sure.
>
> Could you please let me know how we can achieve the parameter sharing in
> mlpack?
>
> Thanks,
>
> Rohan Raj
> Indian Institute of Technology Guwahati
> Assam , India
> Phone : +91 8723990557
>
>
> ᐧ
>
> On Mon, 11 Mar 2019 at 01:11, Ryan Curtin <ryan at ratml.org> wrote:
>
>> On Fri, Mar 08, 2019 at 04:31:55AM +0530, Rohan Raj wrote:
>> > Hello Ryan, Marcus and fellow contributors of MLPACK,
>> >
>> > I am Rohan Raj (Github : mirraaj) <https://github.com/mirraaj>,
>> > undergraduate student from Indian Institute of Technology (IIT)
>> Guwahati. I
>> > am writing this email to you to express my interests in becoming a part
>> of
>> > *MLPACK* for the coming *Google Summer of Codes 2019.*
>> >
>> > I sincerely congratulate Mlpack for being accepted as a mentor
>> organization
>> > for the coming Google Summer of Codes 2019. I am interested in
>> > reinforcement learning project for the coming year. In particular, I
>> plan
>> > to implement Rainbow and PPO for the coming coding season.
>> >
>> > My tentative schedule is present below,
>> >
>> > Week 1-6 : Implement different Rainbow DQN functions
>> >
>> > Week 6-10 : PPO Algorithm
>> >
>> > Week 11-12  Bug fixing and final submission.
>> >
>> > I believe it is really important to test any function/feature added to
>> the
>> > mlpack codebase. I have been working on RL and Mlpack for quite a long
>> time
>> > and I personally think it is difficult to reproduce result sometimes.
>> It is
>> > also a time taking procedure to stabilize statistical test results on
>> > mlpack codebase. Hence I would like to go ahead with 2 algorithms so
>> that I
>> > get proper time to test the algorithms on different environments.
>> >
>> > Please let me know your valuable inputs to this short proposal. I will
>> > definitely add the details of the project in my actual proposal.
>>
>> Hi Rohan,
>>
>> Thanks for the congratulations and we're happy to have you involved.
>> Although I am not a reinforcement learning expert and I won't be the
>> mentor for that project, I will at least say that two weeks set aside
>> for 'bug fixing' is a bit vague---it's definitely hard to predict when
>> you'll have bugs, but as you prepare your proposal I'd encourage you to
>> spend a bit of time thinking about how you will write the tests to catch
>> all potential bugs you might have during implementation.
>>
>> You're right that testing is a very important part, so often when I am
>> reviewing proposals, I look for a lot of detail about how the proposed
>> algorithm will be implemented and things of this nature.
>>
>> I hope this is helpful. :)
>>
>> Thanks!
>>
>> Ryan
>>
>> --
>> Ryan Curtin    | "None of your mailman friends can hear you."
>> ryan at ratml.org |   - Alpha
>>
>
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