AI, OR and Control Theory: A Rosetta Stone for Stochastic Optimization

By Warrren B Powell. 2012

22 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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

Citations in the corpus

• Reinforcement learning in robotics: A survey (2013, background): “Reinforcement learning is very closely related to the theory of classical optimal control, as well as dynamic programming, stochastic programming, simulation-optimization, stochastic search, and optimal stopping (Powell, 2012).”