Vojtěch Kovařík

Artificial Intelligence · 2013–2019

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Reinforcement Learning — 16 citations into it
• Management Science and Operations Research — 15 citations into it
• Game & Decision Theory — 13 citations into it
• Economics and Econometrics — 7 citations into it

Whom Vojtěch Kovařík trusts overall

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

1. Noam Brown
2. Michael L. Littman
3. Michael Bradley Johanson
4. Neil Burch
5. Tuomas Sandholm
6. Michael H. Bowling
7. Martin A. Zinkevich
8. Leslie Pack Kaelbling
9. Yoav Shoham
10. Craig Boutilier

Who trusts Vojtěch Kovařík overall

1. Hengyuan Hu
2. Adam Lerer
3. Kaiqing Zhang

Papers from Vojtěch Kovařík's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Markov Games as a Framework for Multi-Agent Reinforcement Learning
3. Asynchronous Methods for Deep Reinforcement Learning
4. Reinforcement Learning: An Introduction
5. A Course in Game Theory
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Planning and Acting in Partially Observable Stochastic Domains
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers

• Convergence of Monte Carlo Tree Search in Simultaneous Move Games (2013) — 22 citations
• Rethinking Formal Models of Partially Observable Multiagent Decision Making (2019) — 69 citations