Performance

A Practical Performance Budget for Game AI

Published 5 September 2026 · Budget sensing, decisions, planning and navigation without flattening behaviour.

“AI is slow” is not a diagnosis. Separate sensing, decision selection, spatial queries, paths, movement and animation integration.

Choose rates by urgency

Collision response may run frequently; strategic goal selection can run less often or on events. Stagger periodic updates across frames.

Budget asynchronous work

Path and planning queues need latency and throughput targets. Define priority, cancellation and agent behaviour while waiting.

Control fan-out

Perception pairs and candidates grow with agent count. Use spatial partitioning, relevance filters and early rejection. Cache only with explicit assumptions.

Profile quality

Track CPU with reaction latency, stuck time and decision churn on shipping hardware. The archive’s Game AI vs. Traditional AI explains why more CPU alone is not the answer.

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