Takuma joined Sony AI in Oct 2020 as a machine learning engineer, following part-time research positions at Sony R&D Center, Ghelia and Okinawa Institute of Science and Technology. He received his master’s degree in computer science at Keio University in 2019, and is currently pursuing his Ph.D. Takuma’s main research interest is deep reinforcement learning. He developed an offline deep reinforcement learning library, d3rlpy, funded by the IPA MITOU program in 2020, and was certified as a MITOU Super Creator in 2021.


“I am currently working with the Game AI flagship project where we are tackling many practical and theoretical reinforcement learning challenges. There are an enormous number of potential projects where we can leverage the power of reinforcement learning at Sony, and I'm very excited to see what we can do for Sony and the future.”


Expert Human-Level Driving in Gran Turismo Sport Using Deep Reinforcement Learning with Image-based Representation

NeurIPS, 2021
Ryuji Imamura*, Takuma Seno, Kenta Kawamoto, Michael Spranger

When humans play virtual racing games, they use visual environmental information on the game screen to understand the rules within the environments. In contrast, a state-of-the-art realistic racing game AI agent that outperforms human players does not use image-based environ…

d3rlpy: An Offline Deep Reinforcement Learning Library

NeurIPS, 2021
Takuma Seno, Michita Imai*

In this paper, we introduce d3rlpy, an open-sourced offline deep reinforcement learning (RL) library for Python. d3rlpy supports a number of offline deep RL algorithms as well as online algorithms via a user-friendly API. To assist deep RL research and development projects, …


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