Arthur Guez

E455377

Arthur Guez is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Double DQN algorithm.

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Arthur Guez canonical 2

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Predicate Object
instanceOf machine learning researcher
person
affiliation DeepMind reinforcement learning team NERFINISHED
coAuthorOf Bayes-Adaptive Monte-Carlo Planning and Learning in POMDPs NERFINISHED
Bayes-Adaptive Planning in Markov Decision Processes NERFINISHED
Deep Reinforcement Learning with Double Q-learning NERFINISHED
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search NERFINISHED
Information-Theoretic Regret Bounds for Online Nonparametric Regression NERFINISHED
Investigating Model-Free Planning in Human Choice Prediction NERFINISHED
Sample-based Search for Optimal Planning in Markov Decision Processes NERFINISHED
coAuthorWith David Silver NERFINISHED
Hado van Hasselt NERFINISHED
coDeveloperOf Double DQN algorithm NERFINISHED
doctoralThesisTopic Bayes-adaptive planning and learning in Markov decision processes NERFINISHED
educatedAt McGill University NERFINISHED
employer Google DeepMind NERFINISHED
fieldOfWork artificial intelligence
deep reinforcement learning
machine learning
reinforcement learning
gender male
hasAcademicAdvisor Doina Precup NERFINISHED
hasCitation Deep Reinforcement Learning with Double Q-learning (2015) NERFINISHED
knownFor Double DQN algorithm NERFINISHED
memberOf DeepMind NERFINISHED
nationality French
notableWork Deep Reinforcement Learning with Double Q-learning NERFINISHED
researchInterest Monte Carlo tree search NERFINISHED
model-based reinforcement learning
planning in reinforcement learning
worksOn applications of deep RL to games
sample-efficient reinforcement learning

Referenced by (2)

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Double DQN introducedBy Arthur Guez
AlphaGo Zero hasAuthor Arthur Guez