Computational logic in AI: what is the name of the logic that allows computers to represent truth values continuously between 0 and 1, rather than restricting decisions to binary yes/no?

Introduction / Context:
Classical computing often reduces decisions to binary states: true (1) or false (0). Many real-world concepts, however, are gradual—hot vs. warm, tall vs. medium. AI and control systems use alternative logics to capture graded truths and handle uncertainty smoothly.

Given Data / Assumptions:

• The question contrasts binary decision-making with intermediate values.
• We are naming the logic framework that formalizes degrees of truth.
• No specific implementation (e.g., fuzzy controllers) is required, only the concept’s name.

Concept / Approach:
Fuzzy logic represents truth as a continuum in the interval [0, 1]. Membership functions map inputs to degrees of belonging, and rules aggregate these degrees to produce nuanced outputs. This enables smooth control (e.g., in appliances, vehicles) and linguistic reasoning. Boolean logic, by contrast, restricts values to exactly 0 or 1. “Human logic” and “operational logic” are not formal logic systems used for graded truth in computing.

Step-by-Step Solution:

Verification / Alternative check:
Examples include fuzzy temperature control, camera autofocus, and decision support systems using fuzzy inference to handle vagueness.

Why Other Options Are Wrong:

Common Pitfalls:
Confusing probabilistic reasoning (uncertainty about truth) with fuzzy logic (degrees of truth); they are related but distinct.

Final Answer:
Fuzzy logic