Neural Networks in Robotics
By George A. Bekey, Ken Goldberg. 1993
Subfields: Reinforcement Learning
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Reinforcement Learning
- Sergey Levine
- Pieter Abbeel
- Chelsea Finn
- Trevor Darrell
- Abhishek Gupta
- Igor Mordatch
- Anusha Nagabandi
- Vikash Kumar
Citations in the corpus
- End-to-End Training of Deep Visuomotor Policies (2015, methodology): “cement learning dicult (Deisenroth et al., 2013). Pioneering early work on neural network control used 3 Levine, Finn, Darrell, and Abbeel small, simple networks (Pomerleau, 1989; Hunt et al., 1992; Bekey and Goldberg, 1992; Lewis et al., 1998; Bakker et al., 2003; Mayer et al., 2006), and has large”
- Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning (2017, methodology): “Although neural networks were widely used in earlier work to model plant dynamics [15, 2], more recent model-based algorithms have achieved only limited success in applying such models to the more complex benchmark tasks that are commonly used in deep reinforcement learning.”