Quasi-online reinforcement learning for robots
By Bram Bakker, Viktor Zhumatiy, Gabriel Gruener, J. Urgen Schmidhuber. 2006
43 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sergey Levine
- Pieter Abbeel
- J. Bagnell
- Chelsea Finn
- Abhinav Kumar Gupta
- Jan Peters
- Lerrel Pinto
- Jens Kober
In Computer Vision and Pattern Recognition
- Lerrel Pinto
- Abhinav Kumar Gupta
- J. Bagnell
- Martial Hebert
- Jan Peters
- Luc Van Gool
- Jitendra Malik
- Trevor Darrell
In Management Science and Operations Research
- Lerrel Pinto
- Jan Peters
- Arun Venkatraman
- Martial Hebert
- J. Bagnell
- Jens Kober
- Byron Boots
- Sergey Levine
Citations in the corpus
- Reinforcement learning in robotics: A survey (2013, background): “Learning in simulation while the computer is idle and employing directed exploration allows Q-learning to learn a navigation task from scratch in 20 minutes (Bakker et al., 2006).”
- Improved Learning of Dynamics Models for Control (2016, background): “Learning based approaches for controlling robotic systems, or more generally autonomous agents, fall into two primary categories: model-based [1–3] and model-free [4–7].”