M. Chermisi

Reinforcement Learning · 2014

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom M. Chermisi trusts overall

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

  1. Richard S. Sutton
  2. Leo Breiman
  3. Damien Ernst
  4. Peter J. Rousseeuw
  5. John N. Tsitsiklis
  6. Pierre Geurts
  7. Jan Peters
  8. Michail G. Lagoudakis
  9. Andrew Barto

Papers from M. Chermisi's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Least-Squares Policy Iteration
  3. Tree-Based Batch Mode Reinforcement Learning
  4. Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method
  5. Algorithms for Reinforcement Learning
  6. Bagging Predictors
  7. Dynamic Programming and Optimal Control, Two Volume Set
  8. Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding
  9. Reinforcement learning of motor skills with policy gradients
  10. Reinforcement Learning and Dynamic Programming Using Function Approximators

Their papers