Adam Crespi

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Adam Crespi trusts

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

  1. Philip Hingston (in Artificial Intelligence)
  2. Marc G. Bellemare (in Reinforcement Learning)

Papers from Adam Crespi's perspective

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

  1. The Arcade Learning Environment: An Evaluation Platform for General Agents
  2. Human-level control through deep reinforcement learning
  3. Proximal Policy Optimization Algorithms (arXiv.org)
  4. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  5. Unifying Count-Based Exploration and Intrinsic Motivation
  6. Mastering the game of Go with deep neural networks and tree search
  7. Curiosity-Driven Exploration by Self-Supervised Prediction
  8. Rainbow: Combining Improvements in Deep Reinforcement Learning
  9. Deep Reinforcement Learning that Matters
  10. FeUdal Networks for Hierarchical Reinforcement Learning

Their papers