Joseph Modayil

E736831

Joseph Modayil is a researcher in artificial intelligence and reinforcement learning, known for co-authoring the influential Rainbow DQN algorithm that combines multiple DQN improvements into a single unified agent.

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Joseph Modayil canonical 3

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Predicate Object
instanceOf computer scientist
researcher
algorithmContribution Rainbow DQN combines several DQN improvements into one unified agent
linked to: Rainbow DQN
coAuthored Rainbow: Combining Improvements in Deep Reinforcement Learning
linked to: Rainbow DQN
contributedTo combining multiple DQN extensions into a single agent
fieldOfWork artificial intelligence
deep reinforcement learning
reinforcement learning
knownFor co-authoring the Rainbow DQN algorithm
notableWork Rainbow DQN
researchInterest practical improvements to RL algorithms
scalable reinforcement learning systems
value-based deep reinforcement learning
studies sample-efficient reinforcement learning methods
stability and performance of deep RL agents
workFocusesOn deep reinforcement learning algorithms
improvements to Deep Q-Networks (DQN)
value-based reinforcement learning

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Referenced by (3)

Full triples — surface form annotated when it differs from this entity's canonical label.

Rainbow DQN proposedBy Joseph Modayil
Rainbow: Combining Improvements in Deep Reinforcement Learning author Joseph Modayil
subject linked to: Dan Horgan
Bilal Piot hasCoAuthor Joseph Modayil