David J. Wu

Artificial Intelligence · with Brown · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Reinforcement Learning — 28 citations into it
• Game & Decision Theory — 9 citations into it

Whom David J. Wu trusts

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

1. Ming Tan (in Reinforcement Learning)
2. Jakob N. Foerster (in Artificial Intelligence)
3. David Silver (in Reinforcement Learning)

Papers from David J. Wu's perspective

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

1. Dueling Network Architectures for Deep Reinforcement Learning
2. Prioritized Experience Replay
3. Deep Reinforcement Learning with Double Q-Learning
4. Distributed Prioritized Experience Replay
5. Recurrent Experience Replay in Distributed Reinforcement Learning
6. Multi Agent Reinforcement Learning Independent vs Cooperative Agents
7. Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination
8. Dota 2 with Large Scale Deep Reinforcement Learning
9. Value-Decomposition Networks For Cooperative Multi-Agent Learning (arXiv.org)
10. Predicting Pragmatic Reasoning in Language Games

Their papers

• Human-level play in the game of Diplomacy by combining language models with strategic reasoning (2022) — 592 citations
• Off-Belief Learning (2021) — 97 citations