Quality

Testing Game AI with Scenario-Based Automation

Published 5 September 2026 ยท Turn desired behaviours and known failures into repeatable automated scenarios.

Game AI rarely has one exact correct output. Verify invariants and acceptable outcomes, not a brittle sequence of internal nodes.

Build small fixtures

Create minimal maps for perception, doors, cover, path links and squads. Control start state and random seed.

Test properties

  • Agents never enter non-walkable space.
  • Lost perception clears direct tracking.
  • Cancelled tasks release reservations.
  • Decision updates respect budget.
  • A fallback runs when planning fails.

Add soak tests

Run crowds for long periods, change routes and remove targets mid-action. Monitor stuck time, replans, allocations and queue growth.

Keep playtests

Automation finds regressions; humans judge fun and readability. Convert confirmed bugs into focused cases and preserve traces from failures.

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