[mlpack] GSoC 2016 Project: Neuroevolution algorithms

[Nakul Gulati]

Hey Marcus,

Apologies for getting back so late, I was working on the draft for the
proposal. I have shared the proposal with mlpack and would appreciate your
inputs.

At the time Udit implemented the perceptron there wasn't any code to
> implement
> the perceptron using the FNN class.


If there is a need to rewrite the perceptron using the fnn interface, I
would work on that too.

Or the other way. Take a look at the pole balancing problem that could be a
> neat
> test case.


After your mention of the pole balancing problem, I read more about it and
it is regarded as a pseudo-standard benchmark test for neuroevolution
algorithms, so I would implement that as part of testing of the algorithm.

Regards,
Nakul

On Sun, Mar 13, 2016 at 8:25 PM, Marcus Edel <marcus.edel at fu-berlin.de>
wrote:

> Hello Nakul,
>
> I have gone through the literature and have a better understanding of the
> algorithms and also have been spending time with the source code. It took a
> little time but now I am acquainted with the source code. After
> understanding
> the ann code I went ahead to check out the perceptron code to see it in
> action
> but to my surprise perceptron although being a feed forward single layer
> neural
> network doesn't use fnn code, is there a particular reason for it, am I
> missing
> something?
>
>
> At the time Udit implemented the perceptron there wasn't any code to
> implement
> the perceptron using the FNN class.
>
> Also about the GSoC project I feel confident with CNE and NEAT but like
> you had
> mentioned the importance of test cases I would the priority would be to
> implement CNE with test cases and then move to NEAT.
>
>
> Or the other way. Take a look at the pole balancing problem that could be
> a neat
> test case.
>
> I hope this is helpful, let me know if I can clarify anything.
>
> Thanks,
> Marcus
>
>
> On 13 Mar 2016, at 11:53, Nakul Gulati <nakgulati at gmail.com> wrote:
>
> Hey Marcus,
>
> I have gone through the literature and have a better understanding of the
> algorithms and also have been spending time with the source code. It took a
> little time but now I am acquainted with the source code. After
> understanding the ann code I went ahead to check out the perceptron code to
> see it in action but to my surprise perceptron although being a feed
> forward single layer neural network doesn't use fnn code, is there a
> particular reason for it, am I missing something?
>
> Also about the GSoC project I feel confident with CNE and NEAT but like
> you had mentioned the importance of test cases I would the priority would
> be to implement CNE with test cases and then move to NEAT.
>
> Regards,
> Nakul Gulati
> Website <https://nakulgulati.com/> || LinkedIn
> <http://in.linkedin.com/in/nakulgulati> || GitHub
> <https://github.com/nakulgulati/>
>
> On Thu, Mar 10, 2016 at 7:17 PM, Marcus Edel <marcus.edel at fu-berlin.de>
> wrote:
>
>> Hello Nakul,
>>
>> It is a good decision to start with something easy that could be CNE or
>> NEAT.
>> Afterwards, we can use that as a baseline for comparison with other
>> implementation. You should keep in mind, that you have to write tests,
>> for every
>> evolution algorithm you write, and that often takes more time than the
>> actual
>> implementation. Anyway, this year google made draft proposals part of the
>> proposal workflow. So we can comment on your timeline etc. and give
>> feedback
>> once you submitted your application. Also take a look at:
>> http://write.flossmanuals.net/gsocstudentguide/
>>
>> I hope this is helpful. Let me know if I can clarify anything,
>>
>> Thanks,
>> Marcus
>>
>> On 10 Mar 2016, at 04:12, Nakul Gulati <nakgulati at gmail.com> wrote:
>>
>> Hi,
>>
>> I am a final year Computer Science and Engineering student. I am
>> interested in contributing to the project *Neuroevolution algorithms* as
>> part of GSoC 2016. Some of the courses completed which are relevant to this
>> project are: Data Structures and Design and Analysis of Algorithms, Soft
>> Computing and Artificial Neural Networks.
>>
>> In order to get better understanding about the project and mlpack, the
>> following steps were taken:
>>
>>    - Compiled and tested mlpack on OS X
>>    - Compiled and tested nes emulator communication code: during this I
>>    ended up crashing the emulator hosted on mario.urgs.org 4561, link to
>>    issue <https://github.com/zoq/nes/issues/1>. Which was promptly fixed
>>    by Marcus Edel, big shout out to him.
>>
>> Currently I am studying the reading material, starting with the CNE
>> algorithm.
>>
>> For scope of GSoC project I propose to start with the implementation of
>> the CNE algorithm at first and then move to a second (name would be
>> specified soon) if time permits.
>>
>> I have little trouble setting up an exact timeline for the project. I
>> would love to hear your insight about the approach and timeline and if you
>> think what I propose is realistic.
>>
>> --
>> Regards,
>> Nakul Gulati
>> Website <https://nakulgulati.com/> || LinkedIn
>> <http://in.linkedin.com/in/nakulgulati> || GitHub
>> <https://github.com/nakulgulati/>
>> _______________________________________________
>> mlpack mailing list
>> mlpack at cc.gatech.edu
>> https://mailman.cc.gatech.edu/mailman/listinfo/mlpack
>>
>>
>>
>
>
> --
> Regards,
> Nakul Gulati
> Website <https://nakulgulati.com/> || LinkedIn
> <http://in.linkedin.com/in/nakulgulati> || GitHub
> <https://github.com/nakulgulati/>
>
>
>


-- 
Regards,
Nakul Gulati
Website <https://nakulgulati.com> || LinkedIn
<http://in.linkedin.com/in/nakulgulati> || GitHub
<https://github.com/nakulgulati/>
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