Scott Proper

2009–2012

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Scott Proper trusts overall

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

1. Kagan Tumer
2. Matthew E. Taylor
3. Adrian K. Agogino
4. Peter Stone
5. Carlos Guestrin

Who trusts Scott Proper overall

1. Peter Sunehag
2. Guy Lever

Papers from Scott Proper's perspective

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

1. Distributed agent-based air traffic flow management
2. Reinforcement Learning: An Introduction
3. Behavior transfer for value-function-based reinforcement learning
4. Analyzing and visualizing multiagent rewards in dynamic and stochastic domains
5. Human-level control through deep reinforcement learning
6. Learning to predict by the methods of temporal differences
7. Asynchronous Methods for Deep Reinforcement Learning
8. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
9. Trust Region Policy Optimization (International Conference on Machine Learning)
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Modeling difference rewards for multiagent learning (2012) — 36 citations
• Multiagent Transfer Learning via Assignment-Based Decomposition (2009) — 5 citations