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This repository was archived by the owner on Sep 1, 2023. It is now read-only.
I didn't change the algorithm at all, I just put all the logic for "learning cell" selection in one place.
When a column is bursting, we choose a cell to learn on. The current selection process is:
if the column has matching basal segments
use the cell with the best matching basal segment
else use the least used cell.
We should start also considering apical segments. Here's a trivial addition:
if the column has matching basal segments
use the cell with the best matching basal segment
if the column has matching apical segments
use the cell with the best matching apical segment
else use the least used cell.
We could go further and give preference to a cell that has both a matching apical and basal segment. Or maybe a different change makes sense. (e.g. allowing multiple learning cells per segment in some cases?)
I haven't thought through the effects on experiments. It just seems pretty clear that this code is incomplete.