Fresh from the oven, somewhere above the clouds.
Bake a little joy.
Pass it around.
Mallow’s kitchen is floating into a new morning. Suggest a favorite treat, deliver a flour parcel, and watch six little orders turn into something sweet.
A little progress, one thoughtful task at a time.
THE SAME WORLD, A DIFFERENT LITTLE DAY
The same name starts the same world. Your choices write the rest.
MALLOW’S LITTLE DAYBOOK
A peek inside that little brain how the character decides ↗
See the actual inputs and preferences of Mallow’s trained forest. Open this whenever you’re curious; it’s completely optional.
What Mallow sees
Show every input
- Energy
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- Dough
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- Oven seconds
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- Berry orders
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- Cookie orders
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- Twist orders
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- Berry ready
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- Cookie ready
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- Twist ready
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- Focus berry
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- Focus cookie
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- Focus twist
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Your nudge, compared
This comparison runs the same model on the same current state with and without your priority. It does not change the game.
What the model favors now
Live preview, before the next task. The current task finishes first. Scores are learned preferences, not success probabilities; unavailable tasks cannot be chosen. A queued exact request takes precedence if still possible.
The training record is loading.
Mallow uses a forest trained with pytoolz/WSRF to choose tasks. Your nudges change what the model sees. Movement and world rules are coded; the model does not retrain while you play.
Training recipe & resultsFull evaluation recordPython training source