Francisco S. Melo

Reinforcement Learning · with Lopes · 2008–2011

A researcher in the Science corpus: 7 papers; trusts 57 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 51 citations into it; #1,876 of 2,242 by trust here, #2,063 by citations
• Artificial Intelligence — 45 citations into it; #4,687 of 35,345 by trust here, #9,275 by citations
• Control and Systems Engineering — 31 citations into it
• Social Psychology — 26 citations into it
• Developmental and Educational Psychology — 20 citations into it; #6,045 of 8,223 by trust here, #6,892 by citations
• Cognitive Neuroscience — 17 citations into it
• Management Science and Operations Research — 9 citations into it; #2,888 of 11,946 by trust here, #7,638 by citations
• Game & Decision Theory — 8 citations into it; #206 of 249 by trust here, #209 by citations

Whom Francisco S. Melo trusts overall

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

1. Dimitri P. Bertsekas
2. Matthijs T. J. Spaan
3. Richard S. Sutton
4. Michael L. Littman
5. Martin L. Puterman
6. Nikos A. Vlassis
7. Jelle R. Kok
8. Ben J. A. Kröse
9. Satinder Singh
10. Csaba Szepesvari

Who trusts Francisco S. Melo overall

1. Yujing Hu
2. Y. Liu
3. Yang Gao
4. Yann-Michaël De Hauwere
5. Lucian Busoniu
6. Chao Yu
7. Lin F. Yang
8. Chris Amato
9. Manuel Lopes
10. Yusen Zhan

Papers from Francisco S. Melo's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• An analysis of reinforcement learning with function approximation (2008) — 288 citations
• Active Learning for Reward Estimation in Inverse Reinforcement Learning (2009) — 217 citations
• QueryPOMDP: POMDP-Based Communication in Multiagent Systems (2011) — 33 citations
• Decentralized MDPs with sparse interactions (2011) — 108 citations
• Abstraction Levels for Robotic Imitation: Overview and Computational Approaches (2010) — 50 citations
• A Computational Model of Social-Learning Mechanisms (2009) — 28 citations
• Learning of coordination: exploiting sparse interactions in multiagent systems (2009) — 89 citations