Tier 4
Series 304
304D: The Swarm Grid
"If 100 drones each check the position of the other 99 drones to avoid crashing, that is 10,000 checks per frame. The fleet CPU will melt. A Navigator uses Spatial Partitioning (Grid Hashing) to only check neighbors."
The Concept: Spatial Partitioning
Instead of checking everyone against everyone ($O(N^2)$), we divide the world into grid cells.
* **Registration:** Each drone tells the Grid which cell it is in.
* **Query:** "Who is in my cell?" (Checking 5 neighbors instead of 99).
* **Result:** Massive performance gain for flocks and swarms.
* **Registration:** Each drone tells the Grid which cell it is in.
* **Query:** "Who is in my cell?" (Checking 5 neighbors instead of 99).
* **Result:** Massive performance gain for flocks and swarms.
Red Flag Detected
The AI Trap: "The N-Squared Loop"
You ask the AI: "Make the drones avoid each other."
// AI-Generated Code: Exponential Lag
foreach(var droneA in allDrones) {
foreach(var droneB in allDrones) {
// Audit Fail: 100 * 100 = 10,000 Distance Checks!
if (Vector3.Distance(droneA, droneB) < 1f) Avoid();
}
}
This is "The N-Squared Catastrophe." Doubling the unit count Quadruples the CPU load.
Elite Telemetry
Research shows "Elite" teams achieve 15% faster lead times by keeping AI on a "very tight leash."
- Small Batches Solving one problem at a time prevents logic drift.
- Modular Design Localizing the "blast radius" of AI changes.
- Tight Loops Rapid iteration with constant code review.
The Navigator's Correction
Corrective Protocol
// Corrected: O(N) Speed
var key = GetGridKey(transform.position);
foreach(var neighbor in spatialMap[key]) {
Avoid(neighbor);
}
Your Pilot Command
> A skilled Navigator directs the AI to use a Spatial Hash.