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Draft:Soft computing
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Unlike hard computing schemes, which strive for exactness and full truth, soft computing techniques exploit the given tolerance of imprecision, partial truth, and uncertainty for a particular problem. Another common contrast comes from the observation that [[inductive reasoning]] plays a larger role in soft computing than in hard computing.

==References==
{{reflist}}

==Bibliography==

<!--{{sfn|Gudwin|1999|p=32}}-->*{{cite book |last1=Samir |first1=Rov |last2=Chakraborty |first2=Udit |title=Introduction to soft computing : neuro-fuzzy and genetic algorithms |date=3 Jun. 2013 |publisher=Pearson |isbn=978-8131792469 |ref=harv }}
* {{cite book |doi=10.1007/978-3-642-24672-2_1 |isbn=978-3-642-24671-5 |date=2011 |publisher=Springer Berlin Heidelberg |first1=Rudolf |last1=Seising |first2=Veronica | last2=Sanz  |title=From Hard Science and Computing to Soft Science and Computing An Introductory Survey |chapter=From Hard Science and Computing to Soft Science and Computing – an Introductory Survey |volume=273 |conference=Soft Computing in Humanities and Social Sciences |series=Studies in Fuzziness and Soft Computing |ref=harv}}
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* {{cite journal |last1=Zadeh |first1=Lotfi A. url=https://go.galegroup.com/ps/i.do?id=GALE%7CA15061349&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00010782&p=AONE&sw=w |title=Fuzzy Logic, Neural Networks, and Soft Computing| journal= Communications of the ACM|date=March 1994 |volume=37 |number=3| pages 77-84 |ref=harv}}

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