[mlpack] GSoC 2016 Project: Neuroevolution algorithms

Wed Mar 23 18:56:26 EDT 2016

Hey Marcus,

I had updated the proposal for the project *Implement Neuroevolution
Algorithms*. I wanted to know if you had any closing remarks for the same.

Regards,
Nakul

On Thu, Mar 17, 2016 at 9:16 PM, Nakul Gulati <nakgulati at gmail.com> wrote:

> 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/>
>

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