Fuzzy Logic and Decision Trees

Fuzzy logic in its most basic sense is developed through decision tree type analysis. Thus, on a broader scale, it forms the basis for artificial intelligence systems programmed through rules-based inferences.

Generally, the term fuzzy refers to the vast number of scenarios that can be developed in a decision tree-like system. Developing fuzzy logic protocols can require the integration of rule-based programming. These programming rules may be referred to as fuzzy sets since they are developed at the discretion of comprehensive models.

Fuzzy sets may also be more complex. In more complex programming analogies, programmers may have the capability to widen the rules used to determine the inclusion and exclusion of variables. This can result in a wider range of options with less precise rules-based reasoning.

Tip: Fuzzy logic can be used in trading software, where it is used to analyze market data for buy and sell signals.