Sang-Hyeun Park

Reinforcement Learning · 2011–2012

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 9 citations into it

Whom Sang-Hyeun Park trusts overall

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

1. Yufan Zhao

Who trusts Sang-Hyeun Park overall

1. Róbert Istvan Busa-Fekete

Papers from Sang-Hyeun Park's perspective

Ordered by how strongly the researchers Sang-Hyeun Park trusts endorse each paper. Same corpus, a different order for every researcher.

1. Policy Gradient Methods for Reinforcement Learning with Function Approximation
2. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
3. Actor-Critic Algorithms
4. Natural actor-critic algorithms
5. Learning to predict by the methods of temporal differences
6. Reinforcement Learning as Classification: Leveraging Modern Classifiers
7. The WEKA data mining software: an update
8. Reinforcement learning design for cancer clinical trials
9. Approximate Policy Iteration with a Policy Language Bias
10. Label ranking by learning pairwise preferences (Artificial Intelligence)

Their papers

• Preference-based reinforcement learning: a formal framework and a policy iteration algorithm (2012) — 177 citations
• Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning (2011) — 64 citations