Awesome Reinforcement Learning
📄
Papers
🧭
Topics
🔥
Trending
🗺️
Map
🏆
Leaderboards
🎓
Learn
🤖
Ask AI
⋯
More
👥
Authors
📚
Reading Packs
📊
Datasets
🛠️
Tools
📰
News
📝
Blogs
✉️
Newsletter
🎯
Research Radar
🔖
Saved
+ Add Paper
☾
☀
← authors
·
overview
Loading author…
🤖
Ask AI
Nando de Freitas — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Nando de Freitas
31
papers ·
2210
citations ·
59
h-index
Google (United States)
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
2016 · 871 citations
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
2018 · 264 citations
Sample Efficient Actor-Critic with Experience Replay
2016 · 222 citations
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
2018 · 215 citations
Critic Regularized Regression
2020 · 90 citations
Learning to Perform Physics Experiments via Deep Reinforcement Learning
2016 · 55 citations
Scaling data-driven robotics with reward sketching and batch reinforcement learning
2019 · 45 citations
Hyperparameter Selection for Offline Reinforcement Learning
2020 · 43 citations
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
2019 · 24 citations
Reinforced Self-Training (ReST) for Language Modeling
2023 · 18 citations
Offline Learning from Demonstrations and Unlabeled Experience
2020 · 14 citations
Learning Compositional Neural Programs with Recursive Tree Search and Planning
2019 · 13 citations
Semi-supervised reward learning for offline reinforcement learning
2020 · 7 citations
Playing hard exploration games by watching YouTube
2018 · 6 citations
Learning Deep Features in Instrumental Variable Regression
2020 · 6 citations
Top co-authors
Caglar Gulcehre
· 10
Ziyu Wang
· 7
Konrad Zolna
· 6
Tom Le Paine
· 6
Ksenia Konyushkova
· 5
Misha Denil
· 5
Scott Reed
· 5
Yusuf Aytar
· 4
Alexander Novikov
· 3
Arnaud Doucet
· 3
Bobak Shahriari
· 3
Nicolas Heess
· 3
Topics
Offline RL
Value-Based
Model-Based RL
Safe RL
Game AI
Exploration
Policy Gradient
Multi-Agent
Meta-RL
RLHF & Alignment