Construct · 1 fields · 1 citations

deep deterministic policy gradient: a standalone construct

One name. One construct. A landmark on the map.

● anchor · a standalone construct Nearest construct by meaning·not indexed

A single standalone construct; nearby constructs are located against it in the Collider. Tap a field for its definition, unit, and measures.

Reinforcement learning (machine learning)

an off-policy actor-critic algorithm for continuous actions that learns a deterministic policy with deep networks, replay and target networks.

In reinforcement learning (machine learning), deep deterministic policy gradient refers to an off-policy actor-critic algorithm for continuous actions that learns a deterministic policy with deep networks, replay and target networks. This meaning comes from Lillicrap (2015) in arXiv.[1]

Unit
Recovery means
Measured by

Run it through the Collider, or take the citations with you.

See how deep deterministic policy gradient sits against neighbouring constructs in the Collider, or export every reference on this page in one click.

Open in Collider Export BibTeX Report this entry

Nearby constructs

actor-critic1 fields · 1 citationsanchor · a standalone construct gradient4 fields · 4 citationsjingle · one word, four constructs learning6 fields · 14 citationsjingle · one name, six constructs

References

Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., & Wierstra, D. (2015). Continuous control with deep reinforcement learning. arXiv. https://doi.org/10.48550/arxiv.1509.02971

Cited on this page?

Confirm your construct, or correct us.

If your work is cited behind one of these entries, you know better than we do whether we captured the meaning right. Confirm it, suggest an edit, or dispute it, and your name goes on the entry as an author who has checked it, linked to your ORCID.

Claim your construct