Guozhen Tan

Reinforcement Learning · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 26 citations into it
• Artificial Intelligence — 25 citations into it
• Computer Networks and Communications — 9 citations into it
• Sociology and Political Science — 7 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Guozhen Tan trusts overall

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

1. Richard S. Sutton
2. Andrew Barto
3. Craig Boutilier
4. Martin L. Puterman
5. Peter Stone

Papers from Guozhen Tan's perspective

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

1. Reinforcement Learning: An Introduction
2. Markov Decision Processes: Discrete Stochastic Dynamic Programming
3. Multi Agent Reinforcement Learning Independent vs Cooperative Agents
4. The Complexity of Decentralized Control of Markov Decision Processes
5. Recent Advances in Hierarchical Reinforcement Learning
6. The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
7. Q-learning
8. End to End Learning for Self-Driving Cars
9. A Comprehensive Survey of Multiagent Reinforcement Learning
10. Collective dynamics of ‘small-world’ networks

Their papers

• Emotional Multiagent Reinforcement Learning in Spatial Social Dilemmas (2015) — 72 citations
• Distributed Multiagent Coordinated Learning for Autonomous Driving in Highways Based on Dynamic Coordination Graphs (2020) — 125 citations
• Multiagent Learning of Coordination in Loosely Coupled Multiagent Systems (2015) — 46 citations