Which concept deals with reasoning that allows for varying degrees of truth rather than the usual true/false logic?

Fuzzy logic is the concept that introduces a reasoning framework allowing for varying degrees of truth, which means that instead of categorizing statements strictly as true or false, it recognizes a spectrum of truth values that can be somewhat true or somewhat false. This contrasts with traditional binary logic, where statements are either entirely true (1) or entirely false (0).

Fuzzy logic is particularly useful in scenarios involving uncertainty and approximate reasoning, making it applicable in fields such as control systems, artificial intelligence, and decision-making processes. By incorporating degrees of truth, fuzzy logic provides a more nuanced understanding of complex systems where binary classification falls short, enabling better handling of ambiguous or imprecise information.

The other options pertain to different concepts. Granularity refers to the level of detail considered in a dataset or system. An artificial neural network is a computational model inspired by the human brain, designed for pattern recognition and machine learning. An expert system is a software that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a specific domain. These concepts do not inherently deal with degrees of truth in the manner that fuzzy logic does.