# Fuzzy Logic **Domain:** Mathematics / Computing / Decision systems **Doc Type:** Canonical concept node **Maturity:** Developed ## Definition Fuzzy logic represents degrees of membership or truth between the endpoints of completely false and completely true. ## Mechanism and Significance By assigning graded values, fuzzy systems can model categories with soft boundaries and support control or pattern-recognition decisions that strict binary rules handle poorly. ## Evidence Boundary Fuzzy logic is a formal method, not a claim that all truth is relative. Its usefulness depends on the membership functions, data, and problem being modeled. ## Relationships [[wiki/Binary Opposition|Binary Opposition]] · [[wiki/Cognitive Agency|Cognitive Agency]] · [[wiki/Complex Systems|Complex Systems]] ## Simple Reminders, Quotations, and Thoughts > “Fuzzy logic mirrors human intelligence. Shades of gray, used in computer pattern recognition, capture nuance that strict true-or-false logic misses. Thinking in gradients allows wiser judgment.” > **— Bryant McGill**, *Reclaiming Selfishness, Balance, and the Whole Self, Part 1 - Livestream (Jun 2016)* [[reminders/Mathematics/Thinking in Gradients Allows Wiser Judgment by Bryant McGill|Thinking in Gradients Allows Wiser Judgment by Bryant McGill]]