Taeyoung Lee

Reinforcement Learning · with Hostallero · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 31 citations into it
• Artificial Intelligence — 23 citations into it

Whom Taeyoung Lee trusts overall

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

1. Jakob N. Foerster

Papers from Taeyoung Lee's perspective

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

1. Human-level control through deep reinforcement learning
2. Reinforcement Learning: An Introduction
3. Asynchronous Methods for Deep Reinforcement Learning
4. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
5. Policy Gradient Methods for Reinforcement Learning with Function Approximation
6. Temporal Difference Learning and TD-Gammon
7. ImageNet classification with deep convolutional neural networks
8. Learning Multiagent Communication with Backpropagation
9. Long Short-Term Memory
10. Learning to Communicate with Deep Multi-Agent Reinforcement Learning (Neural Information Processing Systems)

Their papers

• Learning to Schedule Communication in Multi-agent Reinforcement Learning (2019) — 257 citations