Gary A. Hewer

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 38 citations into it
• Artificial Intelligence — 30 citations into it

Whom Gary A. Hewer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Ronald J. Williams
3. Jakob N. Foerster
4. G. Tesauro
5. Volodymyr Mnih
6. David Silver
7. Geoffrey E. Hinton
8. Andrew Barto

Papers from Gary A. Hewer's perspective

Ordered by how strongly the researchers Gary A. Hewer trusts endorse each paper. Same corpus, a different order for every researcher.

1. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
2. Reinforcement Learning: An Introduction
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Asynchronous Methods for Deep Reinforcement Learning
6. Human-level control through deep reinforcement learning
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Continuous control with deep reinforcement learning (International Conference on Learning Representations)

Their papers

• CESMA: Centralized Expert Supervises Multi-Agents (2019) — 6 citations