Query

I need a complete and completely minimal mathematical model of how robustness to Knightian Uncertainty emerges in individuals over evolution. This needs to be completely transparent and also extremely practical, i.e., from the theory it should be immediately clear how to apply this to an AI context, e.g., with populations of LLMs, without any experimentation required it should be provable that it will work, i.e., that the proposed process will lead to increasingly robust LLMs to extreme out-of-distribution events. But, most of all the theory must be exceedingly simple to see why it works, and yet insightful.

Run f8ab8fd5 · deepest · started 6/4/2026, 8:54:16 PM

Connecting…
Knowledge graphEach circle is a page explored; lines are references between them; color shows distance from the red starting page. Click a node to open it.

Waiting for Nietzsche to fetch its first pages…

Nodes will appear here as the agent explores.

0 nodes · 0 edges
CompletedModelgpt-5.5
Live status while the run works: pages explored, which answer draft it is on, elapsed time, and the running cost.
Iteration1000 / 1000
Synthesisdraft 3/3
Draft3 / 3
Elapsed5h 46m
Cost$34.1
Nodes = pages found. Edges = links between them. Max depth = furthest hop from the starting page.
Nodes
Edges
Max depth
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