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
Mark Rowland — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Mark Rowland
14
papers ·
173
citations ·
20
h-index
Google DeepMind (United Kingdom) · Google (United Kingdom)
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning
2022 · 150 citations
Understanding and Preventing Capacity Loss in Reinforcement Learning
2022 · 10 citations
The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning
2022 · 3 citations
An Analysis of Quantile Temporal-Difference Learning
2023 · 3 citations
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes
2023 · 2 citations
Learning Dynamics and Generalization in Reinforcement Learning
2022 · 1 citations
Generalised Policy Improvement with Geometric Policy Composition
2022 · 1 citations
Understanding Self-Predictive Learning for Reinforcement Learning
2022 · 1 citations
Bootstrapped Representations in Reinforcement Learning
2023 · 1 citations
Foundations of Multivariate Distributional Reinforcement Learning
2024 · 1 citations
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning
2020
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees
2022
A Distributional Analogue to the Successor Representation
2024
A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
2024
Top co-authors
Will Dabney
· 10
Marc G. Bellemare
· 5
Yunhao Tang
· 5
Clare Lyle
· 4
R\'emi Munos
· 4
Andr\'e Barreto
· 2
Anna Harutyunyan
· 2
Arthur Gretton
· 2
Bernardo \'Avila Pires
· 2
Bilal Piot
· 2
Charline Le Lan
· 2
Daniele Calandriello
· 2
Topics
Value-Based
Model-Based RL
Game AI
Meta-RL
Policy Gradient
Multi-Agent
Safe RL
Exploration