[mlpack] GSoC 2016 Project: Neuroevolution algorithms

Thu Mar 17 11:46:40 EDT 2016

Hey,

Sure I will take a look at the perceptron module, would help me get a
better understanding of the code too.

While read the original paper on NEAT and the implementation of the
algorithm with the paper, the author had used pole balancing and XOR
problem to benchmark the algorithm. Apart from that I will take a look at
the mountain car problem.

Regards,
Nakul

On Thu, Mar 17, 2016 at 8:17 PM, Marcus Edel <marcus.edel at fu-berlin.de>
wrote:

> Hello Nakul,
>
> 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.
>
>
> Thanks for the proposal, we will take a look on the draft in the next days
> and
> make comments.
>
> 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.
>
>
> If you like you can rewrite the perceptron using the ann modules.
>
> 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.
>
>
> Sounds great, there are a couple of other tests that could be interessting
> like:
> the mountain car task.
>
> Thanks,
> Marcus
>
>
> On 17 Mar 2016, at 14:11, Nakul Gulati <nakgulati at gmail.com> wrote:
>
> 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/>
>
>
>

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