2 citations · 3 across the 7 of their papers we have counts for
7 papers
Shortcut Trajectory Planning for Efficient Offline Reinforcement Learning
Guanquan Wang, Yoshimasa Tsuruoka
Diffusion-based trajectory planners have shown strong performance in offline reinforcement learning, but their iterative denoising process often incurs high inference cost. Consist…
Consistency Trajectory Planning: High-Quality and Efficient Trajectory Optimization for Offline Model-Based Reinforcement Learning
Guanquan Wang, Takuya Hiraoka, Yoshimasa Tsuruoka
This paper introduces Consistency Trajectory Planning (CTP), a novel offline model-based reinforcement learning method that leverages the recently proposed Consistency Trajectory M…
Which Experiences Are Influential for RL Agents? Efficiently Estimating The Influence of Experiences
Takuya Hiraoka, Guanquan Wang, Takashi Onishi +1
In reinforcement learning (RL) with experience replay, experiences stored in a replay buffer influence the RL agent's performance. Information about how these experiences influence…
Unsupervised Discovery of Continuous Skills on a Sphere
Takahisa Imagawa, Takuya Hiraoka, Yoshimasa Tsuruoka
Recently, methods for learning diverse skills to generate various behaviors without external rewards have been actively studied as a form of unsupervised reinforcement learning. Ho…
Which Experiences Are Influential for Your Agent? Policy Iteration with Turn-over Dropout
Takuya Hiraoka, Takashi Onishi, Yoshimasa Tsuruoka
In reinforcement learning (RL) with experience replay, experiences stored in a replay buffer influence the RL agent's performance. Information about the influence is valuable for v…
Soft Sensors and Process Control using AI and Dynamic Simulation
Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka
During the operation of a chemical plant, product quality must be consistently maintained, and the production of off-specification products should be minimized. Accordingly, proces…
Railway Operation Rescheduling System via Dynamic Simulation and Reinforcement Learning
Shumpei Kubosawa, Takashi Onishi, Makoto Sakahara +1
The number of railway service disruptions has been increasing owing to intensification of natural disasters. In addition, abrupt changes in social situations such as the COVID-19 p…