Imitative Reinforcement Learning for Soccer Playing Robots

By Tobias Latzke, Sven Behnke, Maren Bennewitz. 2006

19 citations recorded by the source corpus.

Subfields: Artificial Intelligence, 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. Eric P. Xing
3. Pieter Abbeel
4. Jan Peters
5. Jens Kober
6. Xiaodan Liang
7. J. Bagnell
8. Chelsea Finn

In Control and Systems Engineering

1. Jens Kober
2. Jan Peters
3. J. Bagnell
4. Sergey Levine
5. Pieter Abbeel
6. Eric P. Xing
7. Xiaodan Liang
8. Gerhard Neumann

Citations in the corpus

• Reinforcement learning in robotics: A survey (2013, background): “The instructor may provide additional demonstrations in later learning stages (Latzke et al., 2007; Ross et al., 2011a) and which can also be used as differential feedback (Argall et al.”
• CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving (2018, methodology): “However, DQfD is restricted to domains with discrete action spaces, DQfD, [34] and DDPGfD are not applicable for autonomous driving with significant different actor-critics, action spaces and reward definitions.”