{% extends "base.html" %} {% block title %}GameGame learning and native artifacts{% endblock %} {% block page_id %}gamegame_learning{% endblock %} {% block head %}{% endblock %} {% block content %}
Shared Builder datasets and Gym, Bot learned exports, and the actual Hardware Lab practice ladder.
The dataset generator rejudges saved Builder builds and recipes with the installed native game compiler. Detailer recipes are excluded. Gym runs the native Planner and model without placing objects. If this Builder is running, its practice waits while Gym runs, then its prior practice mode is restored and it imports the generated clean recipes. Restoring practice can resume its existing game activity. Actual pause, restoration and ingestion outcomes appear in the result.
Capture the selected running Bot's actual /learned response as the desktop's learned JSON dataset and training-job baseline.
Eleven training tasks and four held-out tasks run against the model and the simulated Hardware Lab. This does not connect physical hardware. Held-out answers and lessons are excluded from training exports.
The native Detailer offers saved recipe/build artifacts and its finishing controls. Its native panel has no Gym or dataset generator.
Graceful Stop preserves completed native results. Accepted writes use their actual result. Sign-out, expiry, or server shutdown closes the owned worker tree and discards output that has not yet been published. Changed native profiles, source code, or saved input files prevent publication.