Reinforcement learning with supervision by a stable controller

By Michael T. Rosenstein, Andrew Barto. 2004

12 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering

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

1. Sergey Levine
2. Jan Peters
3. Pieter Abbeel
4. Jens Kober
5. J. Bagnell
6. Chelsea Finn
7. Gerhard Neumann
8. Vladlen Koltun

In Computational Theory and Mathematics

1. Sergey Levine
2. J. Bagnell
3. Jan Peters
4. Jens Kober
5. Pieter Abbeel
6. J. Urgen Schmidhuber
7. Gerhard Neumann
8. Chelsea Finn

In Control and Systems Engineering

1. Jens Kober
2. Jan Peters
3. J. Bagnell
4. Sergey Levine
5. Pieter Abbeel
6. Gerhard Neumann
7. Marc Peter Deisenroth
8. Stefan Schaal

Citations in the corpus

• Reinforcement learning in robotics: A survey (2013, background): “Rosenstein and Barto (2004) proposed an actor–critic method that additionally features a supervisor in the form of a stable policy.”