Giacomo Calzolari

Reinforcement Learning · 2006–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Giacomo Calzolari trusts overall

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

  1. Roger B. Myerson
  2. Richard S. Sutton
  3. Ido Erev
  4. Michael Wunder
  5. Daan Bloembergen
  6. Andrew Barto

Who trusts Giacomo Calzolari overall

  1. Dirk Bergemann

Papers from Giacomo Calzolari's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Learning from delayed rewards
  3. Multiagent cooperation and competition with deep reinforcement learning
  4. Evolutionary Dynamics of Multi-Agent Learning: A Survey
  5. Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria
  6. Optimal Auction Design
  7. Classes of Multiagent Q-learning Dynamics with epsilon-greedy Exploration
  8. OPTIMAL AUCTION WITH RESALE
  9. Markov Games as a Framework for Multi-Agent Reinforcement Learning
  10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers