Soft computing mimics biology, especially the human brain, to solve problems that cannot be easily decomposed mathematically. It aims to emulate the human approach to tackling problems using fuzzy logic and is commonly used to map the brain and simplify software design.
Soft computing is a branch of computer science that works on the premise that not all solutions to problems can be exactly accurate. It is most commonly associated with processing techniques designed to mimic biology, especially the human brain. Most of the problems faced by soft computing cannot be easily decomposed in a purely mathematical approach.
To understand the concept of soft computing, it is necessary to understand the differences between a computer and the human brain, especially their relative strengths and advantages. The brain works slower when performing a specific task, but is much more adept at considering multiple options at once. Computers can calculate faster, but they’re limited to a more logical approach, one thing and one time.
To give practical examples of these differences, a search engine can search the entire indexed World Wide Web for a particular piece of text in a fraction of a second. A human may not be able to complete the same task with the equivalent amount of printed material in a lifetime. Computers, however, are relatively poor at recognizing an image, such as a face. A human can usually recognize a familiar face in an instant, while recognizing someone they once met a long time ago is also possible within seconds.
This disparity in facial recognition ability is thought to be because humans do a good job of remembering a face as a whole, unlike a computer, which would break down an image into individual pixels and compare them one by one. Meanwhile, the human would be sure to notice enough similarities to be safe in making a strong guess, even if there were some minor or even major differences. A human can usually recognize the face of an old schoolmate, even if it has changed dramatically as he ages; humans do a good job of identifying features that matter, such as eyes and bone structure.
Soft computing aims to emulate the human or other animal’s approach to tackling problems. This can include the use of fuzzy logic, which is in contrast to traditional binary logic where every piece of data is a 1 or a 0, which can be thought of in terms of a flat wrong or right. Fuzzy logic allows you to classify a data in any phase between 0 and 1, equivalent to having infinite degrees of accuracy.
The most common uses of soft computing involve trying to map a biological structure such as the brain. This allows scientists to learn more about how the brain works and how to deal with neurological problems. Soft computing can also be used to simplify the design of software that operates through logic that humans understand. It can also be used as the foundation for a hybrid approach to computing, combining the reasoning abilities of humans with the processing speed and accuracy of a computer.
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