Jeff Huang

Artificial Intelligence · with Littman · 2014–2016

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

Subfields

Whom Jeff Huang trusts

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

  1. Richard S. Sutton (in Reinforcement Learning)
  2. Andrew Barto (in Reinforcement Learning)
  3. Peter Stone (in Artificial Intelligence)

Papers from Jeff Huang's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Algorithms for Inverse Reinforcement Learning
  3. Maximum Entropy Inverse Reinforcement Learning
  4. A survey of robot learning from demonstration
  5. Robot learning from demonstration
  6. The Behavior of Organisms: An Experimental Analysis
  7. Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
  8. Interactively shaping agents via human reinforcement: the TAMER framework
  9. Algorithmic and Human Teaching of Sequential Decision Tasks
  10. Policy Shaping: Integrating Human Feedback with Reinforcement Learning

Their papers