“The real question is not whether machines think, but whether men do.”
B. F. Skinner
Unlike traditional (hard) computing, soft computing is tolerant of imprecision and uncertainty. The principal constituents of soft computing are fuzzy logic, neural computing, evolutionary computing, machine learning and probabilistic reasoning.
The guiding principle of soft computing is to find ways to exploit the imprecision and uncertainty of the relevant domain, to achieve a robust solution. Typically, in academia, the term soft computing is used to cover artificial intelligence and machine learning techniques.
As stated earlier, a primary motivation of the investment community is to increase trading ...