Reinforcement learning· 2018
Recurrent World Models Facilitate Policy Evolution
DOI 10.48550/arxiv.1809.01999arXiv 1803.10122OpenAlex W2890208753
On the reading lists
- #35 in Reinforcement learning (2026 edition)
Why it matters
Popularized learning compact generative environment models and training policies within imagined simulations.
Condensed from the expert lists' notes.
The record
- First released
- 2018 (from arXiv 1803.10122)
- Citations
- 2,233 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.269 · computed rank 681 · consensus 0.44, must-read 0, citations percentile 0.391 (2010s · reinforcement-learning), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.