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Often, the AI engine is split into multiple layers with different responsibilities:

  • Modules at the base are implementations of AI techniques.

  • Capabilities of the characters depend on these AI techniques.

  • Behaviors are expressed in terms of the specific capabilities.

  • Arbitrators coordinate and select the right behaviors.

The implementation of AI systems benefits from similar trends as game engine development, combining flexibility with efficiency:

  • Native code is used for expensive common runtimes.

  • Scripts provide customized layers, simple to implement.

  • Data files store as much information as possible separate from the codebase.

Table 49.2 summarizes patterns for specific problems.

Table 49.2. Common Problems Encountered in Games and AI Techniques to Handle Them


AI Technique

Problem solving

Rule-based system, fuzzy expert system

Sequential control

Finite-state machines variations

Pattern recognition

Decision trees, neural networks

Sequence recognition

Finite-state automata

As far as learning systems are concerned, there are useful guidelines, too:

  • Prefer supervised approaches, especially when realism is hard to express.

  • Levels of magnitude in the feedback guide the learning.

Mixing and matching these ideas should enable us to develop any game AI system in a simple but robust fashion.

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