Contextual Behaviors and Internal Representations Acquired by Reinforcement Learning with a Recurrent Neural Network in a Continuous State and Action Space Task

By Hiroki Utsunomiya, Katsunari Shibata. 2008

24 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Electrical and Electronic Engineering, 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 Artificial Intelligence

1. Sergey Levine
2. Pieter Abbeel
3. Nicolas Manfred Otto Heess
4. Timothy P. Lillicrap
5. Chelsea Finn
6. David Silver
7. Yoshua Bengio
8. Shimon Whiteson

In Cognitive Neuroscience

1. Timothy P. Lillicrap
2. Nicolas Manfred Otto Heess
3. David Silver
4. Jonathan J. Hunt
5. Sergey Levine
6. Pieter Abbeel
7. Yoshua Bengio
8. Geoffrey E. Hinton

In Electrical and Electronic Engineering

1. Nicolas Manfred Otto Heess
2. Timothy P. Lillicrap
3. David Silver
4. Jonathan J. Hunt
5. Sergey Levine
6. Pieter Abbeel
7. Yuxi Li
8. Mohammad Norouzi

In Reinforcement Learning

1. Sergey Levine
2. Pieter Abbeel
3. Nicolas Manfred Otto Heess
4. Timothy P. Lillicrap
5. David Silver
6. Shimon Whiteson
7. Shixiang Shane Gu
8. Ofir Nachum

Citations in the corpus

• Memory-based control with recurrent neural networks (2015, methodology): “[30] trained LSTM-based stochastic policies using Reinforce; [31, 29, 32] used actor-critic architectures.”