Dear mlpack community, I am Aditya Raj, sophomore at IIT MANDI. I am writing to submit my proposal for GSoC 2023 that involves implementing the Asynchronous Advantage Actor-Critic with Kronecker-factored Trust Region (ACKTR) algorithm and multistep Q-learning for reinforcement learning. I have created a detailed project proposal on Google Docs, which you can access through this link: https://docs.google.com/document/d/10vPzwCxUXSXWs7F0pM7OO3x8-9OnRrVsnN4Z5nwl4Gc/edit?usp=sharing. The proposal outlines the tasks involved in the project, as well as my qualifications, experience, and timeline for completing the project.
The project will involve implementing the ACKTR algorithm and integrating it with the multistep Q-learning algorithm to improve the agent's performance and learning efficiency. The project will also involve evaluating the performance of the algorithm on several benchmark environments, such as Atari games and OpenAI Gym environments, and comparing it with other state-of-the-art algorithms. I believe that this project aligns well with the goals of GSoC, as it involves applying cutting-edge technology to a real-world problem that requires sophisticated algorithms and techniques. Please let me know if you have any feedback or suggestions on the project idea. I am open to any feedback you may have, and I would be happy to answer any questions you might have about the proposal. Thank you for your time and consideration. Best Regards, Aditya Raj Github link: https://github.com/aadi-raj _______________________________________________ mlpack mailing list -- mlpack@lists.mlpack.org To unsubscribe send an email to mlpack-le...@lists.mlpack.org %(web_page_url)slistinfo%(cgiext)s/%(_internal_name)s
