Changjie Fan

Reinforcement Learning · 2018–2021

A researcher in the Science corpus: 8 papers; trusts 33 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 136 citations into it; #2,184 of 2,242 by trust here, #1,844 by citations
• Artificial Intelligence — 131 citations into it; #34,260 of 35,345 by trust here, #22,463 by citations
• Management Science and Operations Research — 24 citations into it
• Game & Decision Theory — 19 citations into it
• Computer Science Applications — 13 citations into it

Whom Changjie Fan trusts overall

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

1. Richard S. Sutton
2. Tabish Rashid
3. Geoffrey E. Hinton
4. Volodymyr Mnih
5. Ben J. A. Kröse
6. Francisco S. Melo
7. Yoshua Bengio
8. Michael L. Littman
9. Diederik P. Kingma

Who trusts Changjie Fan overall

1. Shimon Whiteson

Papers from Changjie Fan's perspective

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

1. Reinforcement Learning: An Introduction
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Asynchronous Methods for Deep Reinforcement Learning
6. Et al
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. Continuous control with deep reinforcement learning (International Conference on Learning Representations)

Their papers

• From Few to More: Large-scale Dynamic Multiagent Curriculum Learning (2019) — 141 citations
• Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns (2019) — 34 citations
• Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces (2019) — 84 citations
• Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games (2021) — 20 citations
• Q-value Path Decomposition for Deep Multiagent Reinforcement Learning (2020) — 65 citations
• Action Semantics Network: Considering the Effects of Actions in Multiagent Systems (2019) — 46 citations
• Learning Action-Transferable Policy with Action Embedding (2019) — 22 citations
• Hierarchical Deep Multiagent Reinforcement Learning (2018) — 24 citations