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Artificial Opponents and Behaviour Print

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Making the game act.

WHAT THE GOAL IS

Opponents that are interesting to play against, not opponents that are optimal.

WHY THAT DISTINCTION MATTERS

A perfect opponent is frequently unenjoyable.

WHAT APPROACHES EXIST

State machines, for simple distinct behaviours Behaviour trees, for more complex decision-making Utility systems, scoring options and choosing the best Planning systems, sequencing actions toward goals

WHAT BEHAVIOUR TREES PROVIDE

Readable, editable decision structures that designers can modify.

WHY THEY ARE COMMON

They scale better than state machines without requiring programming for every change.

WHAT PATHFINDING SOLVES

Moving through a world with obstacles.

WHAT THE STANDARD APPROACH IS

Searching a graph representing navigable space.

WHAT A NAVIGATION MESH IS

A representation of walkable surfaces, generated from the level.

WHAT TO BE CAREFUL WITH

Pathfinding cost with many agents Agents crowding and blocking each other Paths that are technically correct and look unnatural

WHAT MAKES BEHAVIOUR READABLE

Telegraphing: showing what is about to happen.

WHY THAT MATTERS

Players must be able to react, which requires warning.

WHAT TO ADD DELIBERATELY

Imperfection, so opponents feel fallible.


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