← Search

Ruonan Jia

2 accepted papers

2024

COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL

ICLR 2024poster

Dyna-style model-based reinforcement learning contains two phases: model rollouts to generate sample for policy learning and real environment exploration using current policy for dynamics model learning. However, due to the complex real-world environment, it is inevitable to learn an imperfect dynam…

Cited by 10SourcePDFScholar
2023

Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy

ICML 2023poster

Model-based reinforcement learning (RL) often achieves higher sample efficiency in practice than model-free RL by learning a dynamics model to generate samples for policy learning. Previous works learn a dynamics model that fits under the empirical state-action visitation distribution for all histor…