Hi MLPack, I’m new to the Github, the mailing list, and the mlpack project but I’ve been going through the source code and the tutorials because I am very interested in contributing to mlpack for GSoC. I had an idea for a GSoC proposal but it’s a bit different from anything on the idea list so I wanted to ask for feedback first.
Recently, DeepMind released a paper called PathNet (https://arxiv.org/pdf/1701.08734.pdf <https://arxiv.org/pdf/1701.08734.pdf>) where they investigate fixing evolution channels as a method for transferring learning between groups of diverse tasks (Atari games). I think an interesting project could be to develop the path fixing algorithms that allow PathNet to transfer learning. I saw that Bang Liu had worked on NEAT in GSoC 2016 but I couldn’t find his project so I’m not sure how much structure there is for neural evolution. I was looking for feedback on how feasible this project could be in terms of support and whether it was something that would be useful to mlpack. I also saw in the mailing list archives that a few people are already interested in implementing DQN, A3C, etc. for GSoC 2017 and I think it could be possible for me to collaborate with them (PathNet was run over A3C in DeepMind’s tests so that is an obvious use case). But I think the majority of this project would be independent of their work as it could hopefully be designed to work with an arbitrary RL training technique. Also, I’m sorry if this was the wrong place to email this. I couldn’t find a way to contact those working on the ANN modules directly. Let me know if there’s a better place for me to ask for feedback on my idea. Best, Michael Gump MIT Class of 2019
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