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Python ETM: Apical segments on predicted cells are reused even if they're not matching

mrcslws opened this issue · comments

commented

There are a few big issues here:

  • Apical segments are never grown from predicted cells. They're only grown from bursting cells.
  • Apical segments on predicted cells will be reused during learning even when they aren't matching. Segments will be overused.
  • Additional bug: No learning happens if all of the cell's segments have 0 active synapses. This line should start with maxActiveSynapses = -1. Of course, this issue will go away when we start using the minThreshold.

This code needs to be much different: https://github.com/numenta/nupic.research/blob/5230a39e3adf9f62aa16d146ad8415d0bfb9f7da/htmresearch/algorithms/extended_temporal_memory.py#L425

It should find the best matching segment, and if there are no matching segments it should grow one.