In contrast to traditional binary true/false states, fuzzy logic allows for degrees of truth. In computer science, it is often used to allow for an entity to exist in multiple mutually-exclusive states as well as allowing for analytic recognition of relative categories.
Traditional logic dictates binary true or false values. Fuzzy logic allows for degrees of truth.
In computer science, fuzzy logic is often used to allow for entities to exist in more than one typically-mutually-exclusive states. An example would be an agent that can be 60% defensive and 40% aggressive. The simplest resolution to this fuzzy state would be allowing the agent a 60% chance of acting defensively, and a 40% chance of acting aggressively.
Fuzzy logic also allows for a realistic understanding of relative categories rather than determining arbitrary thresholds for those categories. An example of this would be a "tall" description of objects. Rather than determining some point beyond which objects are "tall" and before which they are not "tall", a system could recognize an object as 70% tall because it was taller than 70% of objects.
