William Paul

2017

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

Papers from William Paul's perspective

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

  1. Asynchronous Methods for Deep Reinforcement Learning
  2. Human-level control through deep reinforcement learning
  3. Reinforcement Learning: An Introduction
  4. MuJoCo: A physics engine for model-based control
  5. Proximal Policy Optimization Algorithms (arXiv.org)
  6. The Arcade Learning Environment: An Evaluation Platform for General Agents
  7. Mastering the game of Go with deep neural networks and tree search
  8. Benchmarking Deep Reinforcement Learning for Continuous Control
  9. Distributed Prioritized Experience Replay
  10. Deterministic Policy Gradient Algorithms

Their papers