[mlpack] GSoC Proposal for implementing HyperNEAT and es-HyperNEAT

[Rahul Prabhu]

Hey Pranav,
It would be great if my NEAT implementation could be extended. I think you
should focus on CPPNs and HyperNEAT, since it seems infeasible to also
create ES-HyperNEAT in the time left.

CPPN's are pretty nice - off the top of my head, it would be cool if we
could add something to the website where people could use CPPNs to generate
art like on PicBreeder or EndlessForms. It would also be nice to have
HyperNEAT. An issue important to address would be how you could use the
existing NEAT implementation and extend it to HyperNEAT - what changes
would be required, if any.



On Sat, Mar 14, 2020 at 2:34 AM PESALADINNE PRANAV REDDY . <
f20180238 at hyderabad.bits-pilani.ac.in> wrote:

> Hey everyone, My name is Pranav Reddy and my idea for GSoC is to implement
> HyperNEAT and if time permits es-HyperNEAT as well. I feel like this is a
> good idea since as far as I've seen there are so few HyperNEAT
> implementations out there.
>
> All of this would be using the NEAT implementation that was added last
> year as HyperNEAT relies on it. HyperNEAT also involves CPPNs which I plan
> to implement first. Since CPPNs are very similar to ANNs this shouldn't be
> too much of a problem.
> Following which I will implement HyperNEAT based off of the paper
> http://eplex.cs.ucf.edu/publications/2009/stanley-alife09. For this we
> would mainly be applying the NEAT algorithm to a CPPN. I will also be
> implementing a user defined substrate as described in the aforementioned
> paper.
>
> On completion of HyperNEAT, if time permits I would also like to implement
> Evolvable Substrate HyperNEAT() as it builds off of HyperNEAT directly. For
> this, the substrate would also have to evolve with each generation. Further
> details can be found in this paper:
> http://eplex.cs.ucf.edu/publications/2012/risi-alife12. I will only
> complete this if there is time of course but I hope that I am able to.
>
> Of course testing is also a very important part and I will test each
> method in the following ways:
> CPPN :
> I think the best test for this would be creating images using CPPNs to
> view spatial patterns such as bilateral symmetry,  imperfect symmetry,
> repetition with variation, etc. as can be seen here :
> http://picbreeder.org/.
> HyperNeat :
> For now my idea is to test this using the visual discrimination experiment
> in the paper http://eplex.cs.ucf.edu/publications/2009/stanley-alife09.
> If I can think of a better experiment or if anyone has any suggestions I
> will do that.
> es-HyperNEAT:
> As of yet, I have not been able to find any experiment that does not
> involve using robots in a controlled environment so any suggestions for
> this test would be greatly appreciated.
>
> Another reason I think this project would be appropriate is that it is a
> very sequential project which will result in at least something solid being
> merged into the codebase in case everything planned is not completed on
> time. I will provide a more detailed phase by phase implementation
> hopefully in a few days for the same.
> Any suggestions are greatly appreciated. Also sorry if it was a long read.
> Thanks in advance.
>
>
>
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