Jie Fu

Reinforcement Learning · with Topcu · 2014–2017

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 11 citations into it
• Artificial Intelligence — 10 citations into it; #23,687 of 35,345 by trust here, #33,294 by citations
• Statistical Learning Theory — 5 citations into it

Whom Jie Fu trusts overall

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

1. Michael Kearns
2. Ronen I. Brafman
3. Satinder Singh
4. Moshe Tennenholtz
5. Alexander L. Strehl
6. Axel Legay

Who trusts Jie Fu overall

1. Josiah P. Hanna
2. Scott Niekum
3. Peter Stone
4. Oliver Kroemer
5. Dorsa Sadigh
6. Rodrigo Toro Icarte

Papers from Jie Fu's perspective

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

1. Markov Decision Processes: Discrete Stochastic Dynamic Programming
2. Near-Optimal Reinforcement Learning in Polynomial Time
3. R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
4. Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
5. Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
6. Learning from delayed rewards
7. Knows what it knows: a framework for self-aware learning
8. Exploration and apprenticeship learning in reinforcement learning
9. PAC model-free reinforcement learning
10. Neuronlike adaptive elements that can solve difficult learning control problems

Their papers

• Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints (2014) — 196 citations
• Environment-Independent Task Specifications via GLTL (2017) — 162 citations