[mlpack] [GSoC'18] Reinforcement Learning

[VAIBHAV GUPTA]

Hello everyone,

My name is Vaibhav Gupta. I am a 3rd year undergraduate student pursuing my
B.Tech in Computer Science and M.S by research in IIIT Hyderabad, India.

My research domain is Artificial Intelligence, specifically *Reinforcement
Learning & Multi-agent Systems* in Machine Learning Lab, IIIT Hyderabad. I
am doing my research under Prof. Praveen Paruchuri
<https://scholar.google.com/citations?user=ILUqgKEAAAAJ&hl=en> and
Prof. Balaraman
Ravindaran <https://scholar.google.co.in/citations?user=nGUcGrYAAAAJ&hl=en>.
I have past open source experience of contributing to ZENODO(CERN). Also, I
was selected as intern in *The Linux Foundation* where my project revolved
around coming up with various performance metrics for object storage.

I have good understanding of *neural networks* and (as a part of my
academic project). I have also implemented
<https://github.com/guptavaibhav18197/student-teacher-transfer-learning>
the paper - Distilling the knowledge in Neural Network
<https://arxiv.org/abs/1503.02531> in which we try to transfer the learning
of a larger network(teacher) to a relatively smaller network(student)
making use of the logits of the teacher network.

Currently, I am doing research in Reinforcement learning (Transfer
learning) and trying to come up with a state granular confidence metric in
simultaneously learning heterogeneous agents. I have sound knowledge of
many prominent algorithms used in Reinforcement Learning.

I have a sound background in data structures and algorithms and have
qualified twice for *ACM ICPC* regionals. I have secured good rank in other
programming contests too. I have good understanding of *C++* having done
all my competitive programming and several different projects using it.

I have gone through the project idea list of mlpack and found the project
idea Reinforcement Learning really interesting. I have *read papers on
Double DQN /  Playing Atari with deep reinforcement learning* and have
fairly good understanding of these. Attached is the exhaustive list of
papers that I have implemented and read as part of research work.  I am an
enthusiast in reinforcement learning and am ready to read and learn on the
go as the need be.

Since I am new to mlpack please let me know as to how can I get started.
Also since, there are no relevant tickets open at this time, please suggest
me know how to proceed.

Thanks
Vaibhav Gupta
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