feat(SNNBot): add binary reservoir aimer as alternative to SuperSpike (#159)
New architecture: 1024 binary neurons in fixed random reservoir, 72-bin population-coded output, WTA Hebbian learning with binary ops. Forward pass: AND + popcount. Learning: OR (reinforce) / AND NOT (punish). No backprop, no floats in hot path. Toggle via USE_RESERVOIR const. Forecast: ~200-400 ticks to learn stationary target aiming. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -2,15 +2,19 @@
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# 80-input population-coded → 12 LIF hidden → polar-coded (sin/cos) output decoded via atan2.
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# Inputs: bearing [0-35], velocity direction [36-71], speed [72-79].
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# No movement, no firing. SuperSpike three-factor rule on all weights (issue #158).
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# Binary reservoir alternative toggled via USE_RESERVOIR const (issue #159).
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#
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# State machine:
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# DECIDE → feed bearing+velocity into SNN, store targetAngle, → WAITING
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# DECIDE → feed bearing+velocity into SNN/reservoir, store targetAngle, → WAITING
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# WAITING → aimTo() each tick; when error < 2° → EVALUATE
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# EVALUATE → measure error, compute SuperSpike update, log, → DECIDE
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# EVALUATE → measure error, compute SuperSpike/reservoir update, log, → DECIDE
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import std/[math, random, os, strutils]
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import robocode_tankroyale_botapi
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import radar_lock/radar_lock as radar_lock
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import reservoir
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const USE_RESERVOIR* = true
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# ── Constants ──────────────────────────────────────────────────────────────────
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@@ -194,6 +198,7 @@ type
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SNNBot = ref object of Bot
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snn: SNN
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res: Reservoir
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phase: Phase
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targetAngle: float # SNN output (absolute bearing)
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enemyBearing: float # last known enemy bearing
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@@ -370,6 +375,17 @@ method onRoundStarted*(bot: SNNBot, e: RoundStartedEvent) =
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method onGameStarted*(bot: SNNBot, e: GameStartedEventForBot) =
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initSNN(bot.snn)
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bot.res = initReservoir(42)
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# ── Reservoir helpers ─────────────────────────────────────────────────────────
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proc toBitVec80(inputs: array[N_IN, float]): BitVec80 =
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result = [0'u64, 0'u64]
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for i in 0 ..< N_IN:
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if inputs[i] > 0.5:
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let word = i div 64
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let bit = i mod 64
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result[word] = result[word] or (1'u64 shl bit)
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# ── Main loop ─────────────────────────────────────────────────────────────────
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@@ -393,30 +409,38 @@ method run*(bot: SNNBot) =
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let relBearing = normalizeRelativeAngle(bot.enemyBearing - gunDir)
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bot.lastRelBearing = relBearing
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let inputs = encodeInputFull(relBearing, bot.velDirDeg, bot.velSpeed, bot.hasLastPos)
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# Multi-tick inference: accumulate sin/cos and spike counts over N_INFER ticks
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var totalSin = 0.0; var totalCos = 0.0
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var tickSpikes: array[N_HID, float]
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var tickVSnap: array[N_HID, float]
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for h in 0 ..< N_HID: bot.lastSpikes[h] = 0.0
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for _ in 0 ..< N_INFER:
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var sinT, cosT: float
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bot.snn.forward(inputs, tickSpikes, tickVSnap, sinT, cosT)
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totalSin += sinT; totalCos += cosT
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when USE_RESERVOIR:
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let binInput = toBitVec80(inputs)
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let winBin = bot.res.forward(binInput)
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let aimAngle = bot.res.interpolatedAngle(winBin)
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bot.targetAngle = gunDir + aimAngle
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bot.lastDecideGunDir = gunDir
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echo "RES tick=" & $bot.tick & " bin=" & $winBin & " aim=" & formatFloat(aimAngle, ffDecimal, 1)
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else:
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# Multi-tick inference: accumulate sin/cos and spike counts over N_INFER ticks
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var totalSin = 0.0; var totalCos = 0.0
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var tickSpikes: array[N_HID, float]
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var tickVSnap: array[N_HID, float]
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for h in 0 ..< N_HID: bot.lastSpikes[h] = 0.0
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for _ in 0 ..< N_INFER:
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var sinT, cosT: float
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bot.snn.forward(inputs, tickSpikes, tickVSnap, sinT, cosT)
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totalSin += sinT; totalCos += cosT
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for h in 0 ..< N_HID:
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bot.lastSpikes[h] += tickSpikes[h] # accumulate counts
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# Store last-tick voltages for learning
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bot.lastVSnap = tickVSnap
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bot.snn.lastSinOut = totalSin; bot.snn.lastCosOut = totalCos
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bot.snn.lastSnnAngle = arctan2(totalSin, totalCos) * 180.0 / PI
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bot.targetAngle = gunDir + bot.snn.lastSnnAngle
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bot.lastDecideGunDir = gunDir
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# Log total spike count across inference window
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var spikeCount = 0
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var maxV = 0.0
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for h in 0 ..< N_HID:
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bot.lastSpikes[h] += tickSpikes[h] # accumulate counts
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# Store last-tick voltages for learning
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bot.lastVSnap = tickVSnap
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bot.snn.lastSinOut = totalSin; bot.snn.lastCosOut = totalCos
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bot.snn.lastSnnAngle = arctan2(totalSin, totalCos) * 180.0 / PI
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bot.targetAngle = gunDir + bot.snn.lastSnnAngle
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bot.lastDecideGunDir = gunDir
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# Log total spike count across inference window
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var spikeCount = 0
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var maxV = 0.0
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for h in 0 ..< N_HID:
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spikeCount += int(bot.lastSpikes[h])
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maxV = max(maxV, bot.snn.vHid[h])
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echo "tick=" & $bot.tick & " infer_spk=" & $spikeCount & "/" & $(N_INFER * N_HID) & " maxV=" & formatFloat(maxV, ffDecimal, 3)
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spikeCount += int(bot.lastSpikes[h])
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maxV = max(maxV, bot.snn.vHid[h])
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echo "tick=" & $bot.tick & " infer_spk=" & $spikeCount & "/" & $(N_INFER * N_HID) & " maxV=" & formatFloat(maxV, ffDecimal, 3)
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bot.phase = WAITING
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of WAITING:
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@@ -427,33 +451,44 @@ method run*(bot: SNNBot) =
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bot.phase = EVALUATE
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of EVALUATE:
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let err = abs(normalizeRelativeAngle(gunDir - bot.enemyBearing))
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# Predictive error signal: extrapolate enemy position at bullet impact time.
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if bot.hasLastPos:
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let travelTime = bot.enemyDist / BULLET_SPEED
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let velRad = degToRad(bot.velDirDeg)
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let futureX = bot.lastEnemyX + cos(velRad) * bot.velSpeed * travelTime
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let futureY = bot.lastEnemyY + sin(velRad) * bot.velSpeed * travelTime
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let absBearing = directionTo(myX, myY, futureX, futureY)
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let targetAngle = normalizeRelativeAngle(absBearing - bot.lastDecideGunDir)
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bot.snn.superSpikeUpdate(bot.lastSpikes, bot.lastVSnap, bot.snn.preTrace, targetAngle)
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# Compute verbose logging metrics
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var spikeCount = 0
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var maxV = 0.0
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for h in 0 ..< N_HID:
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spikeCount += int(bot.lastSpikes[h])
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maxV = max(maxV, bot.snn.vHid[h])
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var meanWih = 0.0
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for w in bot.snn.wih:
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meanWih += abs(w)
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meanWih /= float(N_IN * N_HID)
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var meanWout = 0.0
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for w in bot.snn.wSin:
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meanWout += abs(w)
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for w in bot.snn.wCos:
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meanWout += abs(w)
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meanWout /= float(2 * N_HID)
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echo "tick=" & $bot.tick & " err=" & formatFloat(err, ffDecimal, 1) & "° infer_spk=" & $spikeCount & "/" & $(N_INFER * N_HID) & " maxV=" & formatFloat(maxV, ffDecimal, 3) & " |wih|=" & formatFloat(meanWih, ffDecimal, 4) & " |wOut|=" & formatFloat(meanWout, ffDecimal, 4) & " sin=" & formatFloat(bot.snn.lastSinOut, ffDecimal, 3) & " cos=" & formatFloat(bot.snn.lastCosOut, ffDecimal, 3) & " snnAngle=" & formatFloat(bot.snn.lastSnnAngle, ffDecimal, 1)
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let absBearing = directionTo(myX, myY, futureX, futureY)
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let targetRel = normalizeRelativeAngle(absBearing - bot.lastDecideGunDir)
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when USE_RESERVOIR:
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let winBin = bot.res.forward(toBitVec80(encodeInputFull(
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normalizeRelativeAngle(bot.enemyBearing - bot.lastDecideGunDir),
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bot.velDirDeg, bot.velSpeed, bot.hasLastPos)))
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let aimAngle = bot.res.interpolatedAngle(winBin)
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bot.res.learn(targetRel)
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echo "RES tick=" & $bot.tick & " bin=" & $winBin &
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" aim=" & formatFloat(aimAngle, ffDecimal, 1) &
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" target=" & formatFloat(targetRel, ffDecimal, 1) &
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" err=" & formatFloat(abs(aimAngle - targetRel), ffDecimal, 1)
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else:
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let err = abs(normalizeRelativeAngle(gunDir - bot.enemyBearing))
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bot.snn.superSpikeUpdate(bot.lastSpikes, bot.lastVSnap, bot.snn.preTrace, targetRel)
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# Compute verbose logging metrics
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var spikeCount = 0
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var maxV = 0.0
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for h in 0 ..< N_HID:
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spikeCount += int(bot.lastSpikes[h])
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maxV = max(maxV, bot.snn.vHid[h])
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var meanWih = 0.0
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for w in bot.snn.wih:
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meanWih += abs(w)
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meanWih /= float(N_IN * N_HID)
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var meanWout = 0.0
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for w in bot.snn.wSin:
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meanWout += abs(w)
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for w in bot.snn.wCos:
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meanWout += abs(w)
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meanWout /= float(2 * N_HID)
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echo "tick=" & $bot.tick & " err=" & formatFloat(err, ffDecimal, 1) & "° infer_spk=" & $spikeCount & "/" & $(N_INFER * N_HID) & " maxV=" & formatFloat(maxV, ffDecimal, 3) & " |wih|=" & formatFloat(meanWih, ffDecimal, 4) & " |wOut|=" & formatFloat(meanWout, ffDecimal, 4) & " sin=" & formatFloat(bot.snn.lastSinOut, ffDecimal, 3) & " cos=" & formatFloat(bot.snn.lastCosOut, ffDecimal, 3) & " snnAngle=" & formatFloat(bot.snn.lastSnnAngle, ffDecimal, 1)
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bot.phase = DECIDE
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# Radar lock
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@@ -0,0 +1,164 @@
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# ponytail: binary reservoir aimer — prototype; if reservoir projection is poor, scale RESERVOIR_SIZE to 4096
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import std/[bitops, math]
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# ── Constants ──────────────────────────────────────────────────────────────────
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const
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RESERVOIR_SIZE* = 1024
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N_BINS* = 72
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BIN_WIDTH* = 5.0
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INPUT_BITS* = 80
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SPARSITY_IN = 0.1
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SPARSITY_REC = 0.05
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# ── Types ──────────────────────────────────────────────────────────────────────
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type
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BitVec80* = array[2, uint64] # 128 bits allocated, lower 80 used
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BitVec* = array[16, uint64] # 1024 bits
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Reservoir* = object
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wIn: array[RESERVOIR_SIZE, BitVec80]
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wRec: array[RESERVOIR_SIZE, BitVec]
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threshold: array[RESERVOIR_SIZE, int]
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state: BitVec
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readout: array[N_BINS, BitVec]
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scores*: array[N_BINS, int]
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rngState: uint64
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# ── PRNG ───────────────────────────────────────────────────────────────────────
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proc nextRand(r: var Reservoir): uint64 {.inline.} =
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var x = r.rngState
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x = x xor (x shl 13)
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x = x xor (x shr 7)
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x = x xor (x shl 17)
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r.rngState = x
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return x
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proc sparseBits(r: var Reservoir, density: float): uint64 =
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## uint64 with approximately density*64 bits set via repeated AND.
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## density=0.1 → ~1 AND needed for 1/2, but we use a direct Bernoulli approach.
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## ponytail: simple loop over 64 bits; replace with table-lookup if init is hot
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result = 0'u64
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let thresh = uint64(density * float(high(uint64)))
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for bit in 0 ..< 64:
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if r.nextRand() < thresh:
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result = result or (1'u64 shl bit)
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proc randomDecayMask(r: var Reservoir): uint64 =
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## ~1% bits set: AND 6 random words (1/2^6 = 1/64 ≈ 1.5% density).
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result = r.nextRand()
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for _ in 0 ..< 5:
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result = result and r.nextRand()
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# ── Init ───────────────────────────────────────────────────────────────────────
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proc initReservoir*(seed: int): Reservoir =
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result.rngState = uint64(seed) or 1'u64 # avoid zero state
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for i in 0 ..< RESERVOIR_SIZE:
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# Input masks: 80 bits across two uint64s (word 0: bits 0-63, word 1: bits 64-79)
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result.wIn[i][0] = sparseBits(result, SPARSITY_IN)
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# Only bits 0-15 of word 1 are meaningful (global bits 64-79)
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result.wIn[i][1] = sparseBits(result, SPARSITY_IN) and 0x0000_0000_0000_FFFF'u64
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for w in 0 ..< 16:
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result.wRec[i][w] = sparseBits(result, SPARSITY_REC)
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let inPop = popcount(result.wIn[i][0]) + popcount(result.wIn[i][1])
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let recPop = block:
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var s = 0
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for w in 0 ..< 16: s += popcount(result.wRec[i][w])
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s
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# Threshold: ~50% of expected input votes + ~30% of expected recurrent votes
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result.threshold[i] = max(1, int(float(inPop) * 0.5 + float(recPop) * 0.3))
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# readout and state are zero-initialized by default
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# ── Forward ────────────────────────────────────────────────────────────────────
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proc forward*(r: var Reservoir, input: BitVec80): int =
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var newState: BitVec
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for i in 0 ..< RESERVOIR_SIZE:
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let inScore = popcount(input[0] and r.wIn[i][0]) +
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popcount(input[1] and r.wIn[i][1])
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var recScore = 0
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for w in 0 ..< 16:
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recScore += popcount(r.state[w] and r.wRec[i][w])
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if inScore + recScore > r.threshold[i]:
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let wordIdx = i shr 6 # i div 64
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let bitIdx = i and 63 # i mod 64
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newState[wordIdx] = newState[wordIdx] or (1'u64 shl bitIdx)
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r.state = newState
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var bestBin = 0
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var bestScore = -1
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for k in 0 ..< N_BINS:
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var score = 0
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for w in 0 ..< 16:
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score += popcount(r.state[w] and r.readout[k][w])
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r.scores[k] = score
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if score > bestScore:
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bestScore = score
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bestBin = k
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return bestBin
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# ── Angle helpers ──────────────────────────────────────────────────────────────
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proc binToAngle*(bin: int): float =
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## Bin 0 = -180°, Bin 36 = 0°, Bin 71 = +175°
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result = -180.0 + float(bin) * BIN_WIDTH
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proc angleToBin*(angle: float): int =
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## angle in -180..+180, map to bin 0..71
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var a = angle
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if a < -180.0: a += 360.0
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if a >= 180.0: a -= 360.0
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result = int((a + 180.0) / BIN_WIDTH) mod N_BINS
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proc interpolatedAngle*(r: Reservoir, winnerBin: int): float =
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## Weighted circular centroid of winner ± 1 bins for sub-5° precision.
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let left = (winnerBin - 1 + N_BINS) mod N_BINS
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let right = (winnerBin + 1) mod N_BINS
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let sW = float(r.scores[winnerBin])
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let sL = float(r.scores[left])
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let sR = float(r.scores[right])
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let total = sW + sL + sR
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if total == 0.0: return binToAngle(winnerBin)
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let aW = degToRad(binToAngle(winnerBin))
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let aL = degToRad(binToAngle(left))
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let aR = degToRad(binToAngle(right))
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let sinAvg = (sW * sin(aW) + sL * sin(aL) + sR * sin(aR)) / total
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let cosAvg = (sW * cos(aW) + sL * cos(aL) + sR * cos(aR)) / total
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result = radToDeg(arctan2(sinAvg, cosAvg))
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# ── Learning ───────────────────────────────────────────────────────────────────
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proc learn*(r: var Reservoir, correctAngle: float) =
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let correctBin = angleToBin(correctAngle)
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# Reinforce correct bin
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for w in 0 ..< 16:
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r.readout[correctBin][w] = r.readout[correctBin][w] or r.state[w]
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# Punish highest-scoring wrong bin
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var worstBin = -1
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var worstScore = -1
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for k in 0 ..< N_BINS:
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if k != correctBin and r.scores[k] > worstScore:
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worstScore = r.scores[k]
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worstBin = k
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if worstBin >= 0:
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for w in 0 ..< 16:
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r.readout[worstBin][w] = r.readout[worstBin][w] and (not r.state[w])
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# Decay: clear ~1.5% of bits per bin to prevent saturation
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for k in 0 ..< N_BINS:
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for w in 0 ..< 16:
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r.readout[k][w] = r.readout[k][w] and (not randomDecayMask(r))
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