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Marcus Hutter — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Marcus Hutter
26
papers ·
474
citations ·
33
h-index
Australian National University · Google DeepMind (United Kingdom) · Google (United Kingdom)
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Most-cited papers
Count-Based Exploration in Feature Space for Reinforcement Learning
2017 · 132 citations
Reinforcement Learning with a Corrupted Reward Channel
2017 · 124 citations
Avoiding Wireheading with Value Reinforcement Learning
2016 · 28 citations
Universal Reinforcement Learning Algorithms: Survey and Experiments
2017 · 20 citations
Thompson Sampling is Asymptotically Optimal in General Environments
2016 · 18 citations
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
2020 · 8 citations
Pessimism About Unknown Unknowns Inspires Conservatism
2020 · 4 citations
Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
2019 · 3 citations
A Strongly Asymptotically Optimal Agent in General Environments
2019 · 2 citations
Conditions on Features for Temporal Difference-Like Methods to Converge
2019 · 2 citations
Distributional Bellman Operators over Mean Embeddings
2023 · 1 citations
Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning
2025
Death and Suicide in Universal Artificial Intelligence
2016
Generalised Discount Functions applied to a Monte-Carlo AImu Implementation
2017
Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent
2020
Top co-authors
Michael K. Cohen
· 5
Tom Everitt
· 5
Elliot Catt
· 3
Jan Leike
· 3
Jarryd Martin
· 2
John Aslanides
· 2
Laurent Orseau
· 2
Matthew Aitchison
· 2
Sultan Javed Majeed
· 2
Victoria Krakovna
· 2
Alaa Saade
· 1
Alexander Meulemans
· 1
Topics
Value-Based
Safe RL
Exploration
Model-Based RL
Meta-RL
RLHF & Alignment
Game AI
Multi-Agent
cs.AI
Policy Gradient