{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "muellerberndt-cadence--imagine-responses-without-changing-live-memory",
 "repo": "muellerberndt/cadence",
 "repo_url": "https://github.com/muellerberndt/cadence",
 "repo_slug": "muellerberndt-cadence",
 "title": "Preview a brain's responses without altering live memory",
 "page_title": "How to preview a brain's responses without altering live memory with Cadence",
 "summary": "Use imagination to inspect possible responses while the live trace and pending feedback stay unchanged.",
 "who": "A developer debugging a Cadence brain who needs to see how it would respond to a sequence of observations without disturbing its ongoing experience.",
 "problem": "Probing a live learning agent often changes its memory or random state, which makes the probe itself corrupt the experiment.",
 "outcome": "A list of imagined phases that can be inspected, with live memory, random state and pending feedback left as they were.",
 "steps": [
  "`python -m pip install cadence-net==0.84.3`",
  "Compose a brain with `brain = Brain.compose(inputs=4, actions=2, arousal=True)` and run a few `live` calls to build some experience.",
  "Pass a list of observation arrays to `brain.imagine([observation, next_observation])`.",
  "Inspect each returned phase, reading `phase.qualified` before using any imagined response.",
  "Continue the live loop and confirm that the next live action is consistent with a run without the imagine call."
 ],
 "agent_prompt": "Using the Python package cadence-net (repo muellerberndt/cadence), compose a brain with inputs=4 and actions=2, run live() for 50 steps, then call imagine() on <observation sequence> and print each phase's qualified flag. Expected output: the qualified flags and the live action taken afterward. Verify that the live action sequence matches a control run that skips imagine().",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The README says imagined responses must be checked for qualification before use, so treat unqualified phases as unreliable.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.11 or newer",
  "NumPy installed through pip",
  "A toy environment or task that can supply an observation and a measured reward after each action"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/muellerberndt-cadence/imagine-responses-without-changing-live-memory/",
 "md": "https://dedupedai.com/use-cases/muellerberndt-cadence/imagine-responses-without-changing-live-memory/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/muellerberndt-cadence--imagine-responses-without-changing-live-memory.json",
 "api_version": "v1"
}