Renke Huang

Reinforcement Learning · 2019

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 8 citations into it

Whom Renke Huang trusts overall

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

1. Stephen W. Carden
2. John Schulman

Papers from Renke Huang's perspective

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

1. Human-level control through deep reinforcement learning
2. Proximal Policy Optimization Algorithms (arXiv.org)
3. OpenAI Gym
4. Deep Reinforcement Learning that Matters
5. Influence of cultivation temperature on the ligninolytic activity of selected fungal strains
6. Constrained Policy Optimization
7. An Introduction to Reinforcement Learning
8. and s
9. Learning Navigation Behaviors End-to-End With AutoRL
10. Sim-to-Real: Learning Agile Locomotion For Quadruped Robots

Their papers

• Adaptive Power System Emergency Control Using Deep Reinforcement Learning (2019) — 348 citations
• The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms (2019) — 345 citations