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Soft computing
{{Distinguish|soft microprocessor}}
{{Expert-subject|computer science|date=July 2009}}

In [[computer science]], '''soft computing''' is the use of inexact solutions to computationally hard tasks such as the solution of [[NP-complete]] problems, for which there is no known algorithm that can compute an exact solution in [[polynomial time]]. Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and [[approximation]]. In effect, the role model for soft computing is the [[human]] [[mind]].

==Introduction==
Soft computing (SC) solutions are unpredictable, uncertain and between 0 and 1. Soft Computing became a formal area of study in Computer Science in the early 1990s.<ref>Zadeh, Lotfi A., "Fuzzy Logic, Neural Networks, and Soft Computing,"  Communication of the ACM, March 1994, Vol. 37 No. 3, pages 77-84.</ref>  Earlier computational approaches could model and precisely analyze only relatively simple systems. More complex systems arising in [[biology]], [[medicine]], t(contracted; show full)* [http://www.softcomputing.es EUROPEAN CENTRE FOR SOFT COMPUTING]
* [http://www.helsinki.fi/~niskanen/bisc.html BISC SIG IN PHILOSOPHY OF SOFT COMPUTING]

{{Authority control}}
[[Category:Scientific modeling]]
[[Category:Artificial intelligence]]
[[Category:Semantic Web]]
[[Category:Soft computing]]