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reduced_fb_recovery

reduced_fb_recovery

Run a bounded soft-mode reduced recovery experiment for forward-backward representations with executable evidence.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: reduced_fb_recovery description: Run a bounded soft-mode reduced recovery experiment for forward-backward representations with executable evidence.

Reduced FB Recovery Evaluation

Use this skill when full environment-scale FB training is blocked but soft-mode recovery permits a declared reduced proxy. It coordinates generated FB skills and records evidence that the mechanism ran.

Inputs

  • Paths to generated FB module scripts.
  • A runtime handoff showing package/model blockers and allowed sources.
  • A small gridworld or transition table for bounded recovery.

Outputs

  • Recovery result JSON with proxy status, metrics, and mechanism checks.
  • Command logs, generated-skill invocation logs, generated data item, and training trace.

Workflow

  1. Load runtime handoff and declare whether full neural/environment training is blocked.
  2. Execute the occupancy factorization skill on reward-free transitions.
  3. Execute reward projection for a late sparse goal.
  4. Execute greedy policy extraction and compare actions to shortest-path oracle moves.
  5. Record before/after loss, parameter changes, skill invocations, and proxy limitations.

Validation

Run the recovery harness and then validate_recovery_experiment.py on the attempt directory. The experiment is acceptable only when the gate reports ok: true.

Limitations

This is proxy evidence and must not be reported as a full paper-scale reproduction. It is designed to prove mechanism fidelity under bounded runtime constraints.

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