feat(BNNBot): shaped reward based on miss distance — every shot teaches something

Replace binary hit/miss reward with exponential decay based on miss distance:
- reward = 2.0 * exp(-missDistance / 36.0) - 1.0
- At 0px: +1.0 (perfect hit)
- At 36px: -0.26 (near miss, small penalty)
- At 100px: -0.87 (big miss, large penalty)

Maintains virtual hit/miss counters for display (threshold: 36px).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

BNNBot_garage/src/BNNBot.nim

@@ -96,12 +96,17 @@ method onScannedBot*(bot: BNNBot, e: ScannedBotEvent) =
     if bulletDist >= b.fireDist or b.trace.age >= TRACE_MAX_AGE:
       let bulletX   = b.fireX + cos(degToRad(b.aimAngleDeg)) * bulletDist
       let bulletY   = b.fireY + sin(degToRad(b.aimAngleDeg)) * bulletDist
-      let enemyDist = hypot(bulletX - bot.lastEnemyX, bulletY - bot.lastEnemyY)
-      if enemyDist < 36.0:
-        bot.net.learn(b.trace, HIT_REWARD)
+      let missDistance = hypot(bulletX - bot.lastEnemyX, bulletY - bot.lastEnemyY)
+
+      # Shaped reward: +1.0 for perfect hit, decays toward -1.0 as miss distance grows
+      # Using exponential decay: reward = 2.0 * exp(-missDistance / 36.0) - 1.0
+      let reward = 2.0 * exp(-missDistance / 36.0) - 1.0
+      bot.net.learn(b.trace, reward)
+
+      # Track hit/miss for display: hit if within 36px, miss otherwise
+      if missDistance < 36.0:
         inc bot.virtualHits
       else:
-        bot.net.learn(b.trace, MISS_PENALTY)
         inc bot.virtualMiss
       b.active = false