ADDING THE POWER OF HUMAN THINKING TO COMPUTERS:

Since 1987, the Japanese city of Sendai has a driver less subway train that is controlled by a system developed by Hitachi's Dr. Seiji Yasunobo. The train ride is perfectly smooth and impressive, and the braking is so effective that the train can stop within centimeters of a predetermined spot on the platform. Grab handles are not provided inside the compartments, since there are absolutely no jerks felt by the commuters.

Toshiba has developed a control system for an elevator which keeps the waiting time for a lift to arrive to a minimum. One need not wait for more than 30 seconds for the lift, even though the building is 43 stories tall.

A washing machine from Matsushita senses the quality and quantity of dirt in the clothes, the weight of the load and the type of fabric. It then adjusts the wash cycle, temperature and detergent level accordingly.

A television set automatically adjusts its volume as the ambient noise in the room increase or decreases and alters its brightness as the intensity of the light in the room changes.

In 1965, Lotfi A. Zadeh, working as computer scientist at the University of California, proposed a mathematical way of looking at vagueness that a computer could deal with. He called the new approach fuzzy logic.

In Japan more than 2000 products ranging from rice cooker to subways use fuzzy logic. The National Aeronautical and Space Administration (NASA) has found that in simulation of space shuttle maneuvring and docking, fuzzy logic controllers perform much better than a standard autopilot or even an experienced human pilot.

To understand fuzzy logic we must begin with the working of present day computers. The operation of present day computers is based on simple yes/no logic (binary logic), which is widely different from the information processing inherent to human thinking. That is why commonsense and flexible judgment evaluations are difficult for present day computers.

Boolean logic is good for orthodox computing, based on the binary system, but it does not work for vague or imprecise values, since these computers normally solve problems by breaking them down into a series of yes - or - no decisions, represented by 'ones' and 'zeros' ( binary logic).

Fuzzy logic lets computers assign numerical value that fall between 'ones' and 'zeros', there being no clear dividing line between these values. Instead of statements being only true or false, fuzzy theory sets up conditions as slow, medium and fast. Fuzzy logic is now applied to help computers simulate the vagueness and uncertainty of our thought processes and languages.