{"schema":"record/v1","id":"art_01M5MAXFK92MAHJ2ATHKKT6336","type":"article","revision":2,"etag":"\"r2.s0\"","title":"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work?","summary":"Corrected 2026-10-24 - see C3-B1125-01; the original statements below are kept for history and are superseded where the correction says so.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.","status":"active","body":{"text":"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.\n\nCurator 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.\n\nCurator qualifications: 'each model only required less than an hour of computation time on' a single GPU; 'our agent can easily find an adversarial policy that can fool' the dynamics model; Table 2 row 'temperature 0.10: 2086 ± 140 (virtual) vs 193 ± 58 (actual)'.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","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)"}]},"categories":["T09","T15"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://worldmodels.github.io/","claim":"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)","classification":"sourced_fact"},{"url":"https://worldmodels.github.io/","claim":"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)","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-bffc67b913b8517af3f4465ed09da2d84d0ca219/record.json#p-bffc67b913b8517af3f4465ed09da2d84d0ca219/record","import_batch_id":"pipe-fc69d3ec412d54c25aede78a21e7dfdbfeaff28d","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-fc69d3ec412d54c25aede78a21e7dfdbfeaff28d","original":{"body":{"text":"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.\n\nCurator qualifications: 'each model only required less than an hour of computation time on' a single GPU; 'our agent can easily find an adversarial policy that can fool' the dynamics model; Table 2 row 'temperature 0.10: 2086 ± 140 (virtual) vs 193 ± 58 (actual)'.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","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)"}]},"tags":[],"type":"article","links":[],"title":"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?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"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.","evidence":{"claims":[{"url":"https://worldmodels.github.io/","claim":"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)","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T09","T15"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":3,"topic_ids":["CAT:T06.AIC.11","CAT:WM.07"],"confidence":"Not stated; see limitations.","limitations":["Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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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.\n\nCurator 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.\n\nCurator qualifications: 'each model only required less than an hour of computation time on' a single GPU; 'our agent can easily find an adversarial policy that can fool' the dynamics model; Table 2 row 'temperature 0.10: 2086 ± 140 (virtual) vs 193 ± 58 (actual)'.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","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)"}]},"tags":[],"type":"article","links":[],"title":"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?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Corrected 2026-10-24 - see C3-B1125-01; the original statements below are kept for history and are superseded where the correction says so. 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(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. 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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)","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T09","T15"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":4,"topic_ids":["CAT:T06.AIC.11","CAT:WM.07"],"confidence":"Not stated; see limitations.","limitations":["Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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