Vincent Thomas

Reinforcement Learning · 2012

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 10 citations into it
• Artificial Intelligence — 8 citations into it; #11,333 of 35,345 by trust here, #25,809 by citations
• Statistical Learning Theory — 5 citations into it

Whom Vincent Thomas trusts overall

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

1. Malcolm J. A. Strens
2. Ronen I. Brafman
3. J. Kolter

Who trusts Vincent Thomas overall

1. Brendan O'Donoghue
2. Kenji Kawaguchi
3. Ian Osband
4. Yasin Abbasi-Yadkori
5. Sergey Levine

Papers from Vincent Thomas's perspective

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

1. Reinforcement Learning: An Introduction
2. Markov Decision Processes: Discrete Stochastic Dynamic Programming
3. R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
4. Near-Optimal Reinforcement Learning in Polynomial Time
5. A Bayesian Framework for Reinforcement Learning
6. A Bayesian Sampling Approach to Exploration in Reinforcement Learning
7. An analytic solution to discrete Bayesian reinforcement learning
8. Near-Bayesian exploration in polynomial time
9. An Introduction to Reinforcement Learning
10. A theory of the learnable

Their papers

• Near-Optimal BRL using Optimistic Local Transitions (2012) — 41 citations