Value Function Decomposition for Iterative Design of Reinforcement Learning Agents

no code implementations • 24 Jun 2022 • James Macglashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone

These value estimates provide insight into an agent's learning and decision-making process and enable new training methods to mitigate common problems.

Decision Making reinforcement-learning +1

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

no code implementations • 11 Nov 2021 • Ryuji Imamura, Takuma Seno, Kenta Kawamoto, Michael Spranger

We demonstrate that the proposed method performs expert human-level vehicle control under high-speed driving scenarios even with game screen images as high-dimensional inputs.

d3rlpy: An Offline Deep Reinforcement Learning Library

2 code implementations • 6 Nov 2021 • Takuma Seno, Michita Imai

In this paper, we introduce d3rlpy, an open-sourced offline deep reinforcement learning (RL) library for Python.

D4RL Offline RL +2

Temporal Difference Weighted Ensemble For Reinforcement Learning

no code implementations • 25 Sep 2019 • Takuma Seno, Michita Imai

Combining multiple function approximators in machine learning models typically leads to better performance and robustness compared with a single function.

reinforcement-learning Reinforcement Learning (RL)