Fuzzy logic is a type of logical connective that may be used in artificial intelligence. It has the ability to handle cases where there are no clear cut distinctions between two or more possible outcomes. There are three primary types of fuzzy logical connectives: And, Or, and Not.
These can be represented with symbols like this: &&, ||, and ! respectively. Fuzzy logic is able to make decisions based on implicit information rather than explicit information which makes it very useful in applications like machine learning. The first type is the And connective which requires that all of its conditions be met for it to execute.
For example, if we wanted a machine to stop running when both temperature and humidity were below 50%, our fuzzy logical expression would look like this: &&(temperature <= 50 || humidity <= 50).
The second type is Or, which will perform an action as long as one or more of its conditions evaluate to true, so in order for the machine’s engine to turn off under these two conditions, dehumidification must reach at least 60% OR there has been 20 minutes with no movement detected by motion sensors. The final kind of fuzzy logic connectives are Not where something won’t happen unless the condition specified evaluates.