Introduction to Fuzzy Logic
In the real world, information is often ambiguous or imprecise. When
we state that it is warm today, the context is necessary to approximate
the temperature. A warm day in January may be -5 degrees Celsius, but a
warm day in August my be 35 degrees. After a long spell of frigid days,
we may call a milder but still chilly day relatively warm.
Human reasoning
filters and interprets information in order to arrive at conclusions or
to dismiss it as inconclusive. Although machines cannot yet handle
imprecise information in the same ways that humans do, computer programs
with fuzzy logic are becoming quite useful when the sheer volume of tasks
defies human analysis and action.
An organized method for dealing with imprecise data is called fuzzy
logic. The data are considered as fuzzy sets. Traditional sets
include or do not include an individual element; there is no other case
than true or false. Fuzzy sets allow partial membership. Fuzzy Logic is
basicly a multivalued logic that allows intermediate values to be defined
between conventional evaluations like yes/no, true/false, black/white,
etc. Notions like rather warm or pretty cold can be formulated
mathematically and processed with the computer. In this way an attempt
is made to apply a more human-like way of thinking in the programming of
computers.
Fuzzy Sets
Back to AI Page
Another term project about fuzzy logic
For more information on the operations of fuzzy sets, fuzzy control,
or applications of fuzzy logic try checking out the FLLL-Home
Page.
Previous pages consolidated and updated by Dan Haase and Ken Huff for
term project in Environmental Systems Engineering
12/8/97