Andrew Sendonaris

Reinforcement Learning · 2003–2017

A researcher in the Science corpus: 4 papers; trusts 12 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 61 citations into it; #2,182 of 2,242 by trust here, #523 by citations
• Artificial Intelligence — 52 citations into it; #34,289 of 35,345 by trust here, #5,458 by citations
• Management Science and Operations Research — 9 citations into it

Whom Andrew Sendonaris trusts overall

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

1. Ezio Biglieri
2. Allen B. Mackenzie

Who trusts Andrew Sendonaris overall

1. Yindi Jing
2. J. Nicholas Laneman
3. John Boyer
4. Ghurumuruhan Ganesan
5. Tairan Wang
6. Todd E. Hunter
7. Johan Karedal
8. Melda Yuksel
9. Hamid Jafarkhani
10. Weifeng Su

Papers from Andrew Sendonaris's perspective

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

1. Asynchronous Methods for Deep Reinforcement Learning
2. Human-level control through deep reinforcement learning
3. The Arcade Learning Environment: An Evaluation Platform for General Agents
4. ImageNet classification with deep convolutional neural networks
5. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
6. End-to-End Training of Deep Visuomotor Policies
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Deep Learning
9. Mastering the game of Go with deep neural networks and tree search
10. Gradient-based learning applied to document recognition

Their papers

• Deep Q-learning From Demonstrations (2017) — 1,289 citations
• Learning from Demonstrations for Real World Reinforcement Learning (2017) — 160 citations
• User cooperation diversity. Part I. System description (2003) — 6,557 citations
• User cooperation diversity. Part II. Implementation aspects and performance analysis (2003) — 3,240 citations