Robert Tyler Loftin

Reinforcement Learning · 2014–2017

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 30 citations into it
• Artificial Intelligence — 22 citations into it
• Control and Systems Engineering — 12 citations into it

Whom Robert Tyler Loftin trusts overall

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

1. W. B. Knox
2. Richard S. Sutton
3. Andrew Barto
4. Peter Stone
5. Brenna D. Argall
6. Charles Lee Isbell Jr.
7. Andrea Lockerd Thomaz
8. Brian D. Ziebart
9. Shane Griffith
10. G. Tesauro

Who trusts Robert Tyler Loftin overall

1. Ruohan Zhang
2. Pararth Shah
3. Sanmit Narvekar
4. Lin Guan
5. Faraz Torabi
6. Stefanie Tellex
7. Dilek Z. Hakkani-Tür

Papers from Robert Tyler Loftin's perspective

Ordered by how strongly the researchers Robert Tyler Loftin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. Algorithms for Inverse Reinforcement Learning
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Maximum Entropy Inverse Reinforcement Learning
7. A survey of robot learning from demonstration
8. Policy Gradient Methods for Reinforcement Learning with Function Approximation
9. Long Short-Term Memory
10. Residual Algorithms: Reinforcement Learning with Function Approximation

Their papers

• Interactive Learning from Policy-Dependent Human Feedback (2017) — 346 citations
• Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning (2015) — 109 citations
• Learning something from nothing: Leveraging implicit human feedback strategies (2014) — 31 citations