Daniel S. Bernstein

Reinforcement Learning · 2000–2004

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Daniel S. Bernstein trusts overall

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

  1. Leonid Peshkin
  2. Edmund H. Durfee
  3. Leslie Pack Kaelbling
  4. Michael L. Littman
  5. Craig Boutilier
  6. Kee-Eung Kim

Who trusts Daniel S. Bernstein overall

  1. Frans Adriaan Oliehoek
  2. Matthijs T. J. Spaan
  3. Sven Seuken
  4. Chris Amato
  5. Shlomo Zilberstein
  6. Nikos A. Vlassis
  7. Jiachen Yang
  8. Jilles Steeve Dibangoye
  9. Mario Bkassiny
  10. Miao Liu

Papers from Daniel S. Bernstein's perspective

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

  1. Markov Games as a Framework for Multi-Agent Reinforcement Learning
  2. The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
  3. Sequential Optimality and Coordination in Multiagent Systems
  4. The Complexity of Decentralized Control of Markov Decision Processes
  5. Nash Q-Learning for General-Sum Stochastic Games
  6. Fast algorithms for finding randomized strategies in game trees
  7. Learning to Cooperate via Policy Search
  8. Distributed Problem Solving and Planning (European Agent Systems Summer School)
  9. Contributions to the Theory of Games
  10. Reinforcement Learning: An Introduction

Their papers