Autonomous blimp control using model-free reinforcement learning in a continuous state and action space
By Axel Rottmann, Christian Plagemann, P. Hilgers, Wolfram Burgard. 2007
43 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Artificial Intelligence
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Jan Peters
- Jens Kober
- J. Bagnell
- Sergey Levine
- Pieter Abbeel
- Gerhard Neumann
- Stefan Schaal
- Siddhartha S. Srinivasa
In Artificial Intelligence
- Sergey Levine
- Jan Peters
- Pieter Abbeel
- Jens Kober
- J. Bagnell
- Chelsea Finn
- Gerhard Neumann
- Vladlen Koltun
Citations in the corpus
- Reinforcement learning in robotics: A survey (2013, methodology): “Hovering with an autonomous blimp (Rottmann et al., 2007) has been achieved by approximation the state–action value function with a GPR. Similarly, another paper shows that grasping can be learned using GPR (Gräve et al., 2010) by additionally taking into account the uncertainty to guide the…”
- Learning Non-stationary System Dynamics Online Using Gaussian Processes (2010, unknown): “[7] and Deisenroth et al.”