Leonard Newnham

Reinforcement Learning · 2013

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Leonard Newnham trusts overall

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

  1. Richard S. Sutton
  2. Stephen W. Carden
  3. N. Schraudolph
  4. Andrew Barto
  5. Leslie Pack Kaelbling
  6. Michael L. Littman
  7. Matthew Jon Grounds
  8. Edwin P. D. Pednault
  9. Dimitri P. Bertsekas
  10. Doina Precup

Papers from Leonard Newnham's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
  3. Planning and Acting in Partially Observable Stochastic Domains
  4. Markov Games as a Framework for Multi-Agent Reinforcement Learning
  5. An Introduction to Reinforcement Learning
  6. Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta
  7. Learning to predict by the methods of temporal differences
  8. Local Gain Adaptation in Stochastic Gradient Descent
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. Gradient-based learning applied to document recognition

Their papers