Maximilian Puelma Touzel

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Reinforcement Learning — 29 citations into it
• Management Science and Operations Research — 15 citations into it

Whom Maximilian Puelma Touzel trusts overall

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

1. Richard S. Sutton

Papers from Maximilian Puelma Touzel's perspective

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

1. Reinforcement Learning: An Introduction
2. Policy Gradient Methods for Reinforcement Learning with Function Approximation
3. Near-Optimal Reinforcement Learning in Polynomial Time
4. Overcoming catastrophic forgetting in neural networks
5. Progressive Neural Networks
6. Near-optimal Regret Bounds for Reinforcement Learning
7. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
8. A Reinforcement Learning Method for Maximizing Undiscounted Rewards
9. On the role of tracking in stationary environments
10. Progress & Compress: A scalable framework for continual learning

Their papers

• Continual Learning In Environments With Polynomial Mixing Times (2021) — 17 citations