What causes AI performance with many agents?

Every agent runs its full decision-making, perception, and pathfinding each frame, so a large number of agents overwhelms the CPU, especially with expensive sensing and pathfinding.

How do I catch this when it only happens for some players?

Capture it automatically from the player's device with the full stack trace, the device and OS, the build, and a breadcrumb trail of what they did. That turns a vague complaint into a specific, reproducible issue you can fix without owning the hardware it happens on.

How to Fix AI Performance with Many Agents

Quick answer: Time-slice AI updates, use level-of-detail AI for distant agents, share perception and pathfinding, and budget how much AI runs per frame.

AI cost with many agents is per-agent thinking every frame. Budgeting it fixes it. Here is how.

How to fix it

1. Time-slice AI updates

Spread agent decision-making across frames so not every agent thinks every frame. Distant or idle agents can update infrequently, keeping the per-frame AI cost bounded regardless of total count.

2. Use AI level of detail

Run full AI only for agents near the player; give distant ones simplified behavior or freeze them. Detailed decision-making for agents the player cannot see is wasted CPU.

3. Share perception and pathfinding

Expensive sensing and pathfinding can be shared — a group path, a shared perception query — rather than computed per agent. Sharing cuts the dominant costs when many agents do similar things.

Catching the ones you can't reproduce

The hardest version of this to fix is the one you can't reproduce — it only happens on a player's hardware, OS, driver, or save state, under conditions that simply aren't present on your machine. A report that says “it crashed” or “it froze” gives you nothing to act on, so the bug survives release after release while quietly costing you players.

Automatic error capture closes that gap. Each failure arrives with its full stack trace, the device and OS, the build number, and a breadcrumb trail of what the player did right before it broke, so even a failure you have never seen becomes a specific, reproducible issue. Fold identical failures into one signature ranked by how many players each hits, and your worklist sorts itself worst-first instead of arriving as a stream of vague complaints.

This is where a tool like Bugnet earns its place. Its SDK captures every error automatically with the full stack trace plus device, OS, memory, build, and game-state context, folds duplicates into one grouped issue with an occurrence count, and ties each to the build it first appeared on — so you fix the problem that hurts the most players first and confirm it is gone when its signature disappears from the next release.

Ship the fix, watch the signature disappear from the next build. That's how you know it's really gone.