Difference between revisions 616197671 and 620077610 on enwiki

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

'''Soft computing''' is a term applied to a field within computer science which is characterized by 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(contracted; show full)such it forms the basis of a considerable amount of [[machine learning]] techniques. Recent trends tend to involve evolutionary and swarm intelligence based algorithms and bio-inspired computation.<ref>X. S. Yang, Z. H. Cui, R. Xiao, A. Gandomi, M. Karamanoglu, Swarm Intelligence and Bio-Inspired Computation: Theory and Applications, Elsevier, (2013).</ref><ref>D. K. Chaturvedi,Soft Computing: Techniques and Its Applications in Electrical Engineering, Springer, (2008).</ref>

There 
is aare main difference between soft computing and possibility. Possibility is used when we don't have enough information to solve a problem but soft computing is used when we don't have enough information about the problem itself. These kinds of problems originate in the human mind with all its doubts, subjectivity and emotions; an example can be determining a suitable temperature for a room to make people feel comfortable.<br />

==Components==
Components of soft computing include:
(contracted; show full)==External links==
* [http://www.softcomputing.es EUROPEAN CENTRE FOR SOFT COMPUTING]
* [http://www.helsinki.fi/~niskanen/bisc.html BISC SIG IN PHILOSOPHY OF SOFT COMPUTING]

[[Category:Scientific modeling]]
[[Category:Artificial intelligence]]
[[Category:Semantic Web]]
[[Category:Soft computing]]