Finally, we arrive at fuzzy logic. Put simply, fuzzy logic refers to approximating outcomes as opposed to arriving at binary conclusions. We can use fuzzy logic and reasoning to add yet another layer of authenticity to our AI.
Let's use a generic bad guy soldier in a first person shooter as our agent to illustrate this basic concept. Whether we are using a finite state machine or a behavior tree, our agent needs to make decisions. Should I move to state x, y, or z? Will this task return true or false? Without fuzzy logic, we'd look at a binary value (true or false, or 0 or 1) to determine the answers to those questions. For example, can our soldier see the player? That's a yes/no binary condition. However, if we ...
