Chia-Man Hung

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Chia-Man Hung trusts

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

  1. Ming Tan (in Reinforcement Learning)

Who trusts Chia-Man Hung

  1. Shimon Whiteson (in Reinforcement Learning)
  2. Wendelin Böhmer (in Reinforcement Learning)
  3. Chongjie Zhang (in Reinforcement Learning)
  4. Tabish Rashid (in Reinforcement Learning)

Papers from Chia-Man Hung's perspective

Ordered by how strongly the researchers Chia-Man Hung trusts endorse each paper. Same corpus, a different order for every researcher.

  1. The Arcade Learning Environment: An Evaluation Platform for General Agents
  2. Multi Agent Reinforcement Learning Independent vs Cooperative Agents
  3. Counterfactual Multi-Agent Policy Gradients (AAAI Conference on Artificial Intelligence)
  4. Deep Recurrent Q-Learning for Partially Observable MDPs
  5. Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
  6. StarCraft II: A New Challenge for Reinforcement Learning
  7. QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
  8. Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
  9. TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games
  10. A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft

Their papers