Skillful control under uncertainty via direct reinforcement learning

By Vijaykumar Gullapalli. 1995

Subfields: Reinforcement Learning

How researchers see this paper

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

In Reinforcement Learning

1. Sergey Levine
2. Pieter Abbeel
3. Chelsea Finn
4. Vikash Kumar
5. Trevor Darrell
6. Abhishek Gupta
7. Li Fei-Fei
8. Jan Peters

Citations in the corpus

• End-to-End Training of Deep Visuomotor Policies (2015, methodology): “rk Reinforcement learning and policy search methods (Gullapalli, 1990; Williams, 1992) have been applied in robotics for playing games such as table tennis (Kober et al., 2010b), object manipulation (Gullapalli, 1995; Peters and Schaal, 2008; Kober et al., 2010a; Deisenroth et al., 2011; Kalakrishna”
• Machine learning of motor skills for robotics (2007, methodology): “Not so suprisingly, they used policy gradient based policy search methods (Gullapalli, 1993a; Gullapalli et al., 1994; Gullapalli, 1995).”
• Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks (2021, background): “Reinforcement learning (RL) has a rich history of being used for robotic control problems on tasks from locomotion [11, 12, 13] to object manipulation [14, 15, 16].”