Reinforcement Learning: Bridging The Gap Between Research and Applications
Michael Panchenko
Reinforcement learning (RL) has great potential for industrial applications, but few mature software frameworks exist to facilitate its use. This talk discusses efforts to improve the software landscape for RL, making it easier for researchers to contribute algorithms and for engineers to apply RL in real-world settings. Specifically, we highlight the open-source library Tianshou, which provides high-level interfaces for painless RL application development along with lower-level APIs that cater to the needs of researchers. By improving RL software, we aim to accelerate research progress and expand RL adoption in industry.
Michael Panchenko
Affiliation: appliedAI Initiative GmbH
Mischa is a researcher with background in physics and mathematics who decided to change course and go into AI (for the sake of falsifiability of ideas). On his path since then he has worked on multiple projects in ML and data analysis and as a bonus gained some experience DevOps and in developing production grade solutions.
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