Difference between revisions 822237273 and 829456327 on enwiki

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

In [[computer science]], '''soft computing''' (sometimes referred to as [[computational intelligence]], though CI does not have an agreed definition) 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 conventi(contracted; show full)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>
<ref>M. Sipper, [http://www.moshesipper.com/machine-nature-the-coming-age-of-bio-inspired-computing.html Machine Nature: The Coming Age of Bio-Inspired Computing], McGraw-Hill, New York, 2002.</ref>

There are main differences 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.

==Components==
Components of soft computing include:
(contracted; show full)* http://dspace.nitrkl.ac.in:8080/dspace/bitstream/2080/1136/1/subudhi.pdf

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