Yang Yu

Reinforcement Learning · with Jiang · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yang Yu trusts

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

  1. Longxin Lin (in Reinforcement Learning)
  2. Sergey Levine (in Artificial Intelligence)
  3. Richard S. Sutton (in Reinforcement Learning)

Papers from Yang Yu's perspective

Ordered by how strongly the researchers Yang Yu 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. MuJoCo: A physics engine for model-based control
  4. Prioritized Experience Replay
  5. Self-improving reactive agents based on reinforcement learning, planning and teaching
  6. Approximately Optimal Approximate Reinforcement Learning
  7. Rainbow: Combining Improvements in Deep Reinforcement Learning
  8. Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor (International Conference on Machine Learning)
  9. Addressing Function Approximation Error in Actor-Critic Methods
  10. Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Their papers