Chapter 11. Rule-Based AI

In this chapter we’re going to study rule-based AI systems. Rule-based AI systems are probably the most widely used AI systems for both real-world and game AI applications. In their simplest form, rule-based systems consist of a set of if-then style rules that are used to make inferences or action decisions. Technically, we’ve already looked at one form of rule-based system in Chapter 9 on finite state machines. There we used rules to handle state transitions. We also looked at another type of rule-based system in the previous chapter on fuzzy logic, Chapter 10.

In this chapter, we’re going to look specifically at rule-based systems that commonly are used in so-called expert systems. Examples of real-world, rule-based expert systems include medical diagnosis, fraud protection, and engineering fault analysis. One advantage of rule-based systems is that they mimic the way people tend to think and reason given a set of known facts and their knowledge about the particular problem domain. Another advantage of this sort of rule-based system is that it is fairly easy to program and manage because the knowledge encoded in the rules is modular and rules can be coded in any order. This gives some flexibility both when coding the system and modifying the system at a later time. These advantages hopefully will become clearer to you as we move through the material in this chapter. Before we get into the details, though, let’s discuss a couple of game examples ...

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