Hi Suryansh
Glad to see you're interested in the project. Just so we are on the same
page, this project is on creating an RL Environment for simulation rather
than implementing an algorithm. There has been previous work
Hello Ahmed
Good start, the proposal looks decent as well. It could surely go through
several improvements. Things like: How it will fit our codebase, emphasis
on docs & thorough testing is a major plus.
Do take some decent time to understand how the APIs work in ensmallen work
especially
Dear mlpack folks
I'm delighted to announce a new project which has been added to the mlpack
GSoC idea list for Reinforcement learning environment generation.
This project relates to Procedural generation of the environment, so that
RL agents can face real world situations. Please do find the
So good! Love that integration with other widely used APIs is being worked
upon.
On Tue, 13 Jul, 2021, 12:39 am Nippun Sharma,
wrote:
> Hi everyone,
> We are almost halfway through GSoC, so I have written a blog about
> the progress of my project.
>
> Please give it a read:
>
Hey Oleksandr,
I do understand the mail wasn't directed at me, but I believe you should
stay. As the mentors said, they can still discuss about the proposal if
need be. Besides, I think your LM-CMA PR is great, perhaps we could work
on that when you feel like it. This will give you a great
Hey all,
First, I must thank the devs for considering my ideas and suggesting the
feasibility of it. After some careful consideration of GSoC timeline I
propose the following:
Adding:
Month 1:
a) Strength Pareto Evolutionary Algorithm II (SPEA-II) : One of the core
multiobjective algorithm along
Thanks for the valuable feedback!
Using the policy-design pattern sounds like a good idea to me, one reason
> why
> we haven't done this for the existing evolution-based optimizers is that
> they slightly
> differ in functionality
>
I was pondering about the same situation. One of the key
Greetings! Team mlpack.
I'm Nanubala Gnana Sai from the Indian Institute of Information Technology,
Sri City. My IRC-Channel ID is @jonpsy. For quite some time, I've been
contributing to mlpack, more specifically to the MOO algorithms of
ensmallen. #269 <https://github.com/mlpack/ensmallen/p
