Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Off-policy RL algorithms can be sample-efficient for continuous control via sample multiple reuse. Retrieved May 24, 2026, from https://4ort.xyz/entity/off-policy-rl-algorithms-can-be-sample-efficient-for-continuous-control-via-sample-multiple-reuse
MLA“Off-policy RL algorithms can be sample-efficient for continuous control via sample multiple reuse.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/off-policy-rl-algorithms-can-be-sample-efficient-for-continuous-control-via-sample-multiple-reuse.
BibTeX@misc{4ortxyz_off-policy-rl-algorithms-can-be-sample-efficient-for-continuous-control-via-sample-multiple-reuse_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Off-policy RL algorithms can be sample-efficient for continuous control via sample multiple reuse}}, year = {2026}, url = {https://4ort.xyz/entity/off-policy-rl-algorithms-can-be-sample-efficient-for-continuous-control-via-sample-multiple-reuse}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Off-policy RL algorithms can be sample-efficient for continuous control via sample multiple reuse — https://4ort.xyz/entity/off-policy-rl-algorithms-can-be-sample-efficient-for-continuous-control-via-sample-multiple-reuse (retrieved 2026-05-24)