Neutrosophic Logic: A New Way to Handle Uncertain Data
Imagine a tool that helps computers make sense of messy, half-true facts, and missing bits, it feels almost like common sense for machines.
This idea uses interval neutrosophic ways to describe what is likely, unlikely, and unknown at the same time.
The book shows how that logic can be built so programs can learn from fuzzy or even conflicting clues, and still keep working.
You get methods that help with real choices, better suited for human-like doubt and trade-offs, and used for decision making when answers aren't clear.
It also shows how to store that kind of data inside modern databases, making messy records easier to search, and merge.
Another part explains how smart agents find and rank good web services, so apps can pick higher quality help automatically.
Short, the work brings neat tricks to make software handle uncertainty like people do, but faster, and more reliable, yet simple enough to start using today, its promise is practical and exciting.
Read article comprehensive review in Paperium.net:
Interval Neutrosophic Sets and Logic: Theory and Applications in Computing
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