Lu Dong

Reinforcement Learning · with Liu · 2020

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 24 citations into it
• Artificial Intelligence — 21 citations into it
• Game & Decision Theory — 5 citations into it

Whom Lu Dong trusts overall

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

1. Richard S. Sutton
2. Hado van Hasselt
3. Ming Tan
4. Christopher J. C. H. Watkins
5. Andrew Barto
6. David Silver

Papers from Lu Dong's perspective

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

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

Their papers

• Reinforcement Learning With Task Decomposition for Cooperative Multiagent Systems (2020) — 89 citations