A small garden. A patient little gardener.
A little care.
A lot of growing.
Pip has a watering can, muddy paws, and a whole garden to tend. Suggest a favorite patch, send a soft shower, and watch a little harvest take shape.
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.
PIP’S LITTLE DAYBOOK
A peek inside that little brain WSRF · indexrng · qrand ↗
See the actual inputs and preferences of Pip’s trained forest. Open this whenever you’re curious; it’s completely optional.
What Pip sees
Show every input
- Water
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- Energy
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- Berry moisture
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- Sunflower moisture
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- Carrot moisture
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- Berry growth
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- Sunflower growth
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- Carrot growth
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- Berry weeds
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- Sunflower weeds
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- Carrot weeds
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- Focus berries
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- Focus sunflowers
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- Focus carrots
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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.
Pip 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