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D4PG: distributed deterministic actors with a distributional critic

Combined deterministic policy gradients with a distributional critic, distributed experience collection, multi-step targets and prioritized replay for continuous-control learning.

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Combined deterministic policy gradients with a distributional critic, distributed experience collection, multi-step targets and prioritized replay for continuous-control learning.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

A synthesis extending DDPG and distributional RL, not invention of their components. Reported robustness and benchmark gains are empirical, not general continuous-control optimality or safety.

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People and systems

Gabriel Barth-Maron; Matthew W. Hoffman; David Budden; Will Dabney; Dan Horgan; Dhruva TB; Alistair Muldal; Nicolas Heess; Timothy Lillicrap

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English catalogue narrative

D4PG: distributed deterministic actors with a distributional critic

Combined deterministic policy gradients with a distributional critic, distributed experience collection, multi-step targets and prioritized replay for continuous-control learning.

Scientific scope

A synthesis extending DDPG and distributional RL, not invention of their components. Reported robustness and benchmark gains are empirical, not general continuous-control optimality or safety.

People and systems

Gabriel Barth-Maron; Matthew W. Hoffman; David Budden; Will Dabney; Dan Horgan; Dhruva TB; Alistair Muldal; Nicolas Heess; Timothy Lillicrap

Original sources