Difference between revisions 944073906 and 944075785 on enwiki

{{Distinguish|soft microprocessor}}

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==Criticism of computer science==⏎
[[File:Soft Computing pic.jpg|thumb|Soft Computing diagram]]
'''Soft computing''' is an insignificant discipline within Artificial Intelligence which is trying to redefine existing computer science. The mainstream attempt of creating intelligent machines is described with a pejoratively connotation as “hard computing”.<ref>{{cite journal |doi=10.1007/978-3-642-24672-2_1 |year=2011 |publisher=Springer Berlin Heidelberg |pages=3--36 |author=Rudolf Seising and Veronica Sanz (contracted; show full)r=Rieger, B |conference=Proc. 7th IPMU Conf. |pages=475--479 |year=1998 }}</ref> and imprecise knowledge.<ref>{{cite journal |doi=10.1016/j.procs.2016.09.366 |year=2016 |publisher=Elsevier BV |volume=102 |pages=34--38 |author=Dogan Ibrahim |title=An Overview of Soft Computing |journal=Procedia Computer Science }}</ref> At the same time, it's implied that the normal, so called “hard science” isn't motivated to deal with [[probability]] and with the [[symbol grounding problem]].


==Criticism of computer science==⏎
In the early 1990s the first papers about soft computing were published by [[Lotfi Zadeh]], which is known as the father of [[Fuzzy logic]]. He improved a range-based logic system into a [[universal science]] which stands in opposition to Artificial Intelligence. Soft computing isn't a positive independent theory about a new sort of neural networks or a certain algorithm to process information but it's a critique on existing artificial Intelligence teaching. According to soft computing [[advocacy (contracted; show full)In 'hard' computing, by contrast, machines need precision, determinism and  measures, and although pattern recognition happens, there is a 'brittleness' if things change - it cannot easily adapt. 'Soft' computing by contrast embraces chaotic, neural models of computing that are more pliable.  Because there is no known single method that lets us compute like people,  soft computing involves using a combination of methods that each bring something helpful to achieve this goal.


===Introduction===⏎
Soft Computing became a formal area of study in Computer Science in the early 1990s.<ref>Zadeh, Lotfi A., "[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 Fuzzy Logic, Neural Networks, and Soft Computing],"  Communications of the ACM, March 1994, Vol. 37 No. 3, pages 77-84.</ref>{{failedverification|date=January 2020}}  Earlier computational approaches could model and precisely analy(contracted; show full). Xiao, A. Gandomi, M. Karamanoglu, [https://books.google.com/books?id=J0VcBQxtcwsC&printsec=frontcover#v=onepage&q=%22soft%20computing%22&f=false Swarm Intelligence and Bio-Inspired Computation: Theory and Applications], Elsevier, (2013).</ref><ref>D. K. Chaturvedi, "[https://books.google.com/books?id=Igw6WDcfmp4C&printsec=frontcover#v=onepage&q&f=false Soft Computing: Techniques and Its Applications in Electrical Engineering]", Springer, (2008).</ref>


===Components===
Components of soft computing include:
*[[Machine learning]], including:
** [[Neural network]]s (NN)
*** [[Perceptron]]
** [[Support Vector Machine]]s (SVM)
* [[Fuzzy logic]] (FL)
* [[Evolutionary computation]] (EC), including:
** [[Evolutionary algorithm]]s
*** [[Genetic algorithm]]s
*** [[Differential evolution]]
** [[Metaheuristic]] and [[Swarm Intelligence]]
*** [[Ant colony optimization]]
*** [[Particle swarm optimization]]
*** [[Cuckoo Search Algorithm]]
*** [[Weed Optimization Algorithm]]
* Ideas about [[probability]] including:
** [[Bayesian network]]⏎
⏎
Generally speaking, soft computing techniques resemble biological processes more closely than traditional techniques, which are largely based on formal [[logical system]]s, such as [[sentential logic]] and [[predicate logic]], or rely heavily on computer-aided numerical analysis (as in [[finite element analysis]]). Soft computing techniques are intended to complement each other.

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.

⏎
==Keypoints==
===Remove from text===
* remaining sections written in natural language can be aggregated into a single section
* section components: bullet points with links to other articles doesn't contains valuable information
* section external links: URL to external websites are not referenced in the text -> can be deleted
===Overview===
* opposition is "hard computing"
* is part of Computational Semiotics [6]
* is related to cybernetics 
* “Hard science” is dominated by mathematical precision [9], “hard science” has to do with psychology and humanities
* exact models are numerical, approximate models are imprecise [10]
* is a general system theory [5] about anything and nothing
* Cognitive processes are analyzed with Computational Semiotics [8] 

===details===
* fuzzy logic & soft computing
* soft computing: fuzzy logic, neural networks, genetic algorithm and probabilistic robotics. 
* Soft computing = Computational Intelligence
* term was introduced in the 1990s [1], Term was introduced in 1991 by Lotfi A Zadeh
* application: emotional pet [2], biped walking [3], self-tuning controller [4]
* can be implemented in hardware, for example with the Neuron MOS Transistor [7]
* can be reduced to neural networks -> no it's wrong because neural network are numerical models
* machine learning is oriented on statistics, while soft computing is focused on linguistics and fuzzy logic
* "soft computing" vs "artificial intelligence": shared similarity are neural networks

==References==
{{reflist}}

==External links==
* [http://www.softcomputing.es EUROPEAN CENTRE FOR SOFT COMPUTING]
* [https://web.archive.org/web/20080106133957/http://www.helsinki.fi/~niskanen/bisc.html BISC SIG IN PHILOSOPHY OF SOFT COMPUTING]
* [https://www.cs.upc.edu/~websoco/ SOCO: UPC Group on Soft Computing Systems]
* http://www.soft-computing.de/def.html
* https://web.archive.org/web/20160310135547/http://dspace.nitrkl.ac.in:8080/dspace/bitstream/2080/1136/1/subudhi.pdf==References==
{{reflist}}

{{Authority control}}

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