Lixin Xu

Lixin Xu

Self-motivated student researcher and practitioner in robotics

Posts by Tags

CoRL

[Paper Notes] DayDreamer: World Models for Physical Robot Learning - CoRL 2022

1 minute read

Published:

Key information

  • This paper learns two models: a world model trained on off-policy sequences through supervised learning, and an actor-critic model to learn behaviors from trajectories predicted by the learned model.
  • The data collection and learning updates are decoupled, enabling fast training without waiting for the environment. A learner thread continuously trains the world model and actor-critic behavior, while an actor thread in parallel computes actions for environment interaction.

RSS

Reinforcement Learning

[Paper Notes] DayDreamer: World Models for Physical Robot Learning - CoRL 2022

1 minute read

Published:

Key information

  • This paper learns two models: a world model trained on off-policy sequences through supervised learning, and an actor-critic model to learn behaviors from trajectories predicted by the learned model.
  • The data collection and learning updates are decoupled, enabling fast training without waiting for the environment. A learner thread continuously trains the world model and actor-critic behavior, while an actor thread in parallel computes actions for environment interaction.

Robotics

[Paper Notes] DayDreamer: World Models for Physical Robot Learning - CoRL 2022

1 minute read

Published:

Key information

  • This paper learns two models: a world model trained on off-policy sequences through supervised learning, and an actor-critic model to learn behaviors from trajectories predicted by the learned model.
  • The data collection and learning updates are decoupled, enabling fast training without waiting for the environment. A learner thread continuously trains the world model and actor-critic behavior, while an actor thread in parallel computes actions for environment interaction.