{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "sparticle62ops-pssa--run-boxes-world-recurrent-model-experiment",
 "repo": "Sparticle62ops/pssa",
 "repo_url": "https://github.com/Sparticle62ops/pssa",
 "repo_slug": "sparticle62ops-pssa",
 "title": "Run the boxes-world recurrent model experiment",
 "page_title": "How to run the boxes-world recurrent model experiment with Pssa",
 "summary": "Train an RSSM-style PSSA against a plain autoregressive control on a tiny box-pushing grid.",
 "who": "A research engineer studying recurrent world models who wants a small, bounded experiment to compare against a plain control.",
 "problem": "Testing whether stochastic latents help a recurrent model needs a controlled setup with a fair baseline, which is slow to build from scratch.",
 "outcome": "Held-out next-frame NLL, open-loop NLL, accuracy, reward and continuation Brier scores, and timing for both models in one report.",
 "steps": [
  "Build the Pssa binary from the repository. (inferred, check the README)",
  "Run `pssa world-model` for the default bounded experiment.",
  "Run `pssa world-model --seed 73 --train-episodes 32 --heldout-episodes 12 --epochs 3` to change the seed and episode counts.",
  "Run `pssa world-model --help` to see grid size, widths, learning rate, and other settings.",
  "Compare the RSSM-style model with the plain control in the report, and note that the comparison is not parameter or time matched."
 ],
 "agent_prompt": "In the Sparticle62ops/pssa repository, run `pssa world-model --seed <seed> --train-episodes 32 --heldout-episodes 12 --epochs 3`. Report the held-out next-frame NLL for the RSSM-style model and the plain control. Verify that the report states the comparison is not parameter or time matched before drawing any conclusion.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The README says neither model solved the task at the default budget and the stochastic model was about 4.5 times slower, so this is a research probe, not an agent or planning benchmark.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "rust",
 "requirements": [
  "A Rust toolchain (inferred from the Rust implementation and the cargo commands in the README)",
  "The pssa binary built from the Sparticle62ops/pssa repository",
  "A plain UTF-8 text file to train on",
  "A terminal that supports the TUI, or use --no-tui for plain logs"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.6,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/sparticle62ops-pssa/run-boxes-world-recurrent-model-experiment/",
 "md": "https://dedupedai.com/use-cases/sparticle62ops-pssa/run-boxes-world-recurrent-model-experiment/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/sparticle62ops-pssa--run-boxes-world-recurrent-model-experiment.json",
 "api_version": "v1"
}