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
- Artificial Intelligence — 14 citations into it
- Reinforcement Learning — 13 citations into it
Whom Jeff Huang trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton (in Reinforcement Learning)
- Andrew Barto (in Reinforcement Learning)
- 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.
- Reinforcement Learning: An Introduction
- Algorithms for Inverse Reinforcement Learning
- Maximum Entropy Inverse Reinforcement Learning
- A survey of robot learning from demonstration
- Robot learning from demonstration
- The Behavior of Organisms: An Experimental Analysis
- Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
- Interactively shaping agents via human reinforcement: the TAMER framework
- Algorithmic and Human Teaching of Sequential Decision Tasks
- Policy Shaping: Integrating Human Feedback with Reinforcement Learning
Their papers
- Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning (2015) — 109 citations
- WebGazer: Scalable Webcam Eye Tracking Using User Interactions (2016) — 328 citations
- Learning something from nothing: Leveraging implicit human feedback strategies (2014) — 31 citations