There are times when we have to deal with gray areas, instead of binary-based values, to make decisions, and fuzzy logic is a set of mathematical techniques that help us with this task.
Imagine that we're developing an automated driver. A couple of available actions are steering and speed control, both of which have a range of degrees. Deciding how to take a turn, and at which speed, is what will make our driver different and possibly smarter. That's the type of gray area that fuzzy logic helps represent and handle.
This recipe requires a set of states indexed by continuous integer numbers. As this representation varies from game to game, we handle the raw input from such states, along with their fuzzification, in order to have a good general-purpose fuzzy decision maker. Finally, the decision maker returns a set of fuzzy values representing the degree of membership of each state.