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Christian Schroeder de Witt — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Christian Schroeder de Witt
22
papers ·
895
citations ·
10
h-index
University of Oxford · Science Oxford
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
2018 · 475 citations
Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
2020 · 185 citations
Discovered Policy Optimisation
2022 · 16 citations
Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem
2019 · 7 citations
Mirror Learning: A Unifying Framework of Policy Optimisation
2022 · 6 citations
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
2023 · 2 citations
DEEDEE: Fast and Scalable Out-of-Distribution Dynamics Detection
2025
Mitigating Goal Misgeneralization via Minimax Regret
2025
Communicating via Markov Decision Processes
2021
Revealing Robust Oil and Gas Company Macro-Strategies using Deep Multi-Agent Reinforcement Learning
2022
Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
2023
Bayesian Exploration Networks
2023
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection
2024
Top co-authors
Shimon Whiteson
· 6
Jakob Foerster
· 5
Chris Lu
· 2
Jakob Nicolaus Foerster
· 2
Jakub Grudzien Kuba
· 2
Mikayel Samvelyan
· 2
Samuel Sokota
· 2
Akbir Khan
· 1
Alexander Rutherford
· 1
Alexandra Souly
· 1
Alistair Letcher
· 1
Andrei Lupu
· 1
Topics
Safe RL
Multi-Agent
Model-Based RL
Game AI
Exploration
Value-Based
Policy Gradient
Meta-RL
RLHF & Alignment