From 42b6cebd8e32a497d1078692ab1a4166c94620c0 Mon Sep 17 00:00:00 2001
From: Davide Cappellini <signorsasso@gmail.com>
Date: Mon, 14 Sep 2026 22:28:41 +0200
Subject: [PATCH] fix(SNNBot): average matured snapshot targets instead of
 multiple updates

Multiple superSpikeUpdate calls per EVALUATE caused oscillation by
effectively multiplying the learning rate. Now: accumulate retroTarget
via circular mean across all matured snapshots, apply one update with
the averaged target and most recent snapshot's SNN state.
---
 SNNBot_garage/src/SNNBot.nim | 25 +++++++++++++++++++++----
 1 file changed, 21 insertions(+), 4 deletions(-)

diff --git a/SNNBot_garage/src/SNNBot.nim b/SNNBot_garage/src/SNNBot.nim
index 65ae93c..73d2b03 100644
--- a/SNNBot_garage/src/SNNBot.nim
+++ b/SNNBot_garage/src/SNNBot.nim
@@ -464,9 +464,16 @@ method run*(bot: SNNBot) =
       # Retroactive would-have-hit error signal: find the most recently matured snapshot.
       # A snapshot matures when currentTick >= snapshotTick + ceil(distance / BULLET_SPEED).
       # Look up enemy position at impact tick from ring buffer (offset from most-recent write).
-      var retroTarget = bot.lastRelBearing  # fallback; overwritten by each matured snapshot (last one used for logging)
+      var retroTarget = bot.lastRelBearing  # fallback; overwritten after averaging (used for logging)
       var hasMatured = false
       var keepIdx = 0  # first non-matured snapshot to keep
+      # Accumulate retroTarget circular components across all matured snapshots.
+      var sumSin = 0.0; var sumCos = 0.0
+      var matureCount = 0
+      # Most-recent matured snapshot's SNN state (most relevant for weight update).
+      var bestSpikes:   array[N_HID, float]
+      var bestVSnap:    array[N_HID, float]
+      var bestPreTrace: array[N_IN, float]
       for i in 0 ..< bot.snapshots.len:
         let snap = bot.snapshots[i]
         let travelTicks = int(ceil(snap.distance / BULLET_SPEED))
@@ -483,13 +490,23 @@ method run*(bot: SNNBot) =
             let ex = bot.posBuf[foundSlot].x
             let ey = bot.posBuf[foundSlot].y
             let absBearing = directionTo(snap.botX, snap.botY, ex, ey)
-            retroTarget = normalizeRelativeAngle(absBearing - snap.gunHeading)
-            # Update weights for every matured snapshot immediately; earlier ones were previously discarded.
-            bot.snn.superSpikeUpdate(snap.spikes, snap.vSnap, snap.preTrace, retroTarget)
+            let rt = normalizeRelativeAngle(absBearing - snap.gunHeading)
+            # Accumulate circular mean components
+            sumSin += sin(degToRad(rt))
+            sumCos += cos(degToRad(rt))
+            inc matureCount
+            # Keep most-recent (highest index) snapshot's SNN state
+            bestSpikes   = snap.spikes
+            bestVSnap    = snap.vSnap
+            bestPreTrace = snap.preTrace
             hasMatured = true
           keepIdx = i + 1  # discard matured snapshots up to and including this one
         else:
           break  # snapshots are in order; stop at first non-matured
+      # One update per EVALUATE using circular-mean target — stable learning rate regardless of snapshot count.
+      if matureCount > 0:
+        retroTarget = arctan2(sumSin, sumCos) * 180.0 / PI
+        bot.snn.superSpikeUpdate(bestSpikes, bestVSnap, bestPreTrace, retroTarget)
       # Discard matured snapshots; immature ones are preserved automatically (keepIdx stays 0
       # or points past the last matured entry; the rest of bot.snapshots is kept intact).
       if keepIdx > 0: