Yuval Tassa

E441110

computer scientist researcher

Yuval Tassa is a researcher in reinforcement learning and control who co-authored the work that introduced the Deep Deterministic Policy Gradient (DDPG) algorithm.

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All labels observed (1)

Label	Occurrences
Yuval Tassa canonical	1

Statements (46)

Predicate	Object
instanceOf	computer scientist ⓘ researcher ⓘ
coAuthorOf	Continuous control with deep reinforcement learning NERFINISHED ⓘ
coAuthorWith	Alexander Pritzel NERFINISHED ⓘ Andrej A. Rusu NERFINISHED ⓘ Daan Wierstra NERFINISHED ⓘ David Silver NERFINISHED ⓘ Demis Hassabis NERFINISHED ⓘ Guillaume Desjardins NERFINISHED ⓘ Jonathan J. Hunt NERFINISHED ⓘ Koray Kavukcuoglu NERFINISHED ⓘ Martin Riedmiller NERFINISHED ⓘ Nando de Freitas NERFINISHED ⓘ Nicolas Heess NERFINISHED ⓘ Raia Hadsell NERFINISHED ⓘ Sergey Levine NERFINISHED ⓘ Shakir Mohamed NERFINISHED ⓘ Timothy P. Lillicrap NERFINISHED ⓘ Tom Erez NERFINISHED ⓘ Tom Schaul NERFINISHED ⓘ
contributedTo	applications of deep RL to continuous control tasks ⓘ development of DDPG ⓘ
fieldOfWork	control theory ⓘ reinforcement learning ⓘ robotics ⓘ
hasPublicationType	conference papers ⓘ journal articles ⓘ preprints ⓘ
hasResearchInterest	continuous control ⓘ control in high-dimensional systems ⓘ deep reinforcement learning ⓘ deterministic policy gradients ⓘ model predictive control ⓘ model-based control ⓘ motor control ⓘ optimal control ⓘ policy gradient methods ⓘ robot control ⓘ simulation for control ⓘ trajectory optimization ⓘ
knownFor	DDPG algorithm NERFINISHED ⓘ Deep Deterministic Policy Gradient NERFINISHED ⓘ
worksOn	continuous action spaces ⓘ deep learning for control ⓘ neural network policies ⓘ simulation-based reinforcement learning ⓘ

Referenced by (1)

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

DDPG → introducedBy → Yuval Tassa ⓘ