What does 'world model' mean in the 2018 Ha & Schmidhuber paper that many later papers cite, and how does its Vision/Memory/Controller design work?
Corrected 2026-10-24 - see C3-B1125-01; the original statements below are kept for history and are superseded where the correction says so. In Ha & Schmidhuber (arXiv v4) a world model is a learned generative model of an RL environment: a VAE (V) compresses each frame to a latent z, an MDN-RNN (M) predicts the next z given the action, and a tiny linear controller (C) picks actions from z and M's hidden state. The paper shows C can be trained inside M's generated 'dream' and then transferred, and that this fails when C exploits M's errors unless the model's temperature is raised. The meaning is a latent-dynamics model for control on small game environments, not a video or 3D generator. Schmidhuber's 1989-90 'model network' reports are the cited lineage; the phrase 'world model' is the 2018 paper's usage.
Structured fields
{
"citations": [
{
"url": "https://worldmodels.github.io/",
"note": "arXiv 1803.10122v4 PDF (pdftotext -layout lines 249, 492, 555)"
},
{
"url": "https://arxiv.org/abs/1803.10122v4",
"note": "arXiv 1803.10122v4 PDF (pdftotext -layout lines 249, 492, 555)"
},
{
"url": "https://people.idsia.ch/~juergen/FKI-126-90_(revised)bw_ocr.pdf",
"note": "arXiv 1803.10122v4 PDF (pdftotext -layout lines 249, 492, 555)"
}
]
}Evidence claims
- [sourced_fact] Curator correction 2026-10-24 (discovery audit record C3-B1125-01, curator-reviewed C3R-0712; excerpts re-located by independent curator GET 2026-10-24): Correction. Two statements in C3-B003-W1-01 were wrong when written (not later changes). (1) The record says the phrase 'world model' is the 2018 paper's usage and that the 1989-90 reports use the wording 'model network' / 'adaptive model of the environmental dynamics'. The revised report FKI-126-90 (a revision of Feb 1990 and Nov 1989 reports, per its own note) mostly says 'model network' but also uses 'world model' itself, in its curiosity and boredom section: it says the algorithm 'builds a world model for goal-directed learning of the controller' and that 'the world model adapts itself'. The lineage point stands; the phrase is not new in 2018. (2) The record's first method says 'Train V on ~10,000 random-rollout frames'. The paper's procedure for both CarRacing and Take Cover is 'Collect 10,000 rollouts from a random policy', so the unit is rollouts (whole episodes), not frames; the passages read give no frame total. Checked 2026-10-24 against the arXiv v4 PDF and the IDSIA OCR PDF. · locator: curator correction paragraph in this record body (C3-B1125-01) source
- [sourced_fact] SUPERSEDED IN PART 2026-10-24 by curator correction C3-B1125-01 (see the correction claim above); original kept for history: In Ha & Schmidhuber (arXiv v4) a world model is a learned generative model of an RL environment: a VAE (V) compresses each frame to a latent z, an MDN-RNN (M) predicts the next z given the action, and a tiny linear controller (C) picks actions from z and M's hidden state. The paper shows C can be trained inside M's generated 'dream' and then transferred, and that this fails when C exploits M's errors unless the model's temperature is raised. The meaning is a latent-dynamics model for control on small game environments, not a video or 3D generator. Schmidhuber's 1989-90 'model network' reports are the cited lineage; the phrase 'world model' is the 2018 paper's usage. · locator: arXiv 1803.10122v4 PDF (pdftotext -layout lines 249, 492, 555) source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |