Page 127 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Unit 6: Formalized Symbolic Logics

Linguistic Variables Notes

While variables in mathematics usually take numerical values, in fuzzy logic applications, the
non-numeric linguistic variables are often used to facilitate the expression of rules and facts. A
linguistic variable such as age may have a value such as young or its antonym old. However, the
great utility of linguistic variables is that they can be modified via linguistic hedges applied to
primary terms. The linguistic hedges can be associated with certain functions.

Early Applications

The Japanese were the first to utilize fuzzy logic for practical applications. The first notable
application was on the high-speed train in Sendai, in which fuzzy logic was able to improve the
economy, comfort, and precision of the ride. It has also been used in recognition of hand written
symbols in Sony pocket computers, Canon auto-focus technology, Omron auto-aiming cameras,
earthquake prediction and modeling at the Institute of Seismology Bureau of Metrology in
Japan, etc.

Example: Fuzzy set theory defines fuzzy operators on fuzzy sets. The problem in applying
this is that the appropriate fuzzy operator may not be known. For this reason, fuzzy logic
usually uses IF-THEN rules, or constructs that are equivalent, such as fuzzy associative matrices.
Rules are usually expressed in the form:

IF variable IS property THEN action
For example, a simple temperature regulator that uses a fan might look like this:
IF temperature IS very cold THEN stop fan
IF temperature IS cold THEN turn down fan
IF temperature IS normal THEN maintain level
IF temperature IS hot THEN speed up fan
There is no “ELSE” – all of the rules are evaluated, because the temperature might be “cold” and
“normal” at the same time to different degrees.
The AND, OR, and NOT operators of boolean logic exist in fuzzy logic, usually defined as the
minimum, maximum, and complement; when they are defined this way, they are called the
Zadeh operators. So for the fuzzy variables x and y:
NOT x = (1 - truth(x))
x AND y = minimum(truth(x), truth(y))
x OR y = maximum(truth(x), truth(y))

Self Assessment

State whether the following statements are true or false:
23. Fuzzy logic is a form of many-valued logic or probabilistic logic.
24. Fuzzy logics however had been studied since the 1940s as infinite-valued logics notably
by Lukasiewicz and Tarski.

6.13 Natural Language Computation

Natural language processing (NLP) is a field of computer science, artificial intelligence, and
linguistics concerned with the interactions between computers and human (natural) languages.
As such, NLP is related to the area of human – computer interaction. Many challenges in NLP
involve natural language understanding – that is, enabling computers to derive meaning from

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