self-review 2026-06-04: lower WM threshold, soften inhibition, add wm_avg_weight builtin

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Three targeted improvements based on graph health analysis (29K nodes, 104 edges):

1. ENGRAM_WM_THRESHOLD 0.15 → 0.08: sparse graph means BFS paths carry weak
   signals (0.05-0.12 range). Prior threshold gatekept too aggressively. Grounded
   in TBRS* cognitive model (θ=0.05); 0.08 is conservative but effective.

2. ENGRAM_INHIBITION_FACTOR 0.1 → 0.2: factor=0.1 (90% suppression) on a sparse
   graph almost always fully silences targeted nodes. Factor=0.2 (80% suppression)
   maintains strong inhibition while allowing partially-suppressed nodes to remain
   faintly active — consistent with partial inhibition in cognitive neuroscience.

3. engram_wm_avg_weight() builtin: computes mean working_memory_weight of all
   promoted nodes. Returns float bits via el_from_float for EL float_to_str usage.
   Makes activation quality directly observable in heartbeat ISEs, distinguishing
   'many weak activations' (sparse, low avg) from 'few strong' (dense, high avg).

Rebuilt engram binary with new runtime.

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This commit is contained in:

Will Anderson

2026-06-04 08:38:32 -05:00

parent 412bd2744e

commit 1264af72a6

3 changed files with 34 additions and 2 deletions

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