Perceptual computing: Difference between revisions

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==Perceptual computer==

The ''perceptual computer'' – ''Per-C'' – an instantiation of perceptual computing – has the architecture that is depicted in Fig. 1 [2]–[6]. It consists of three components: encoder, CWW engine and decoder. Perceptions – words – activate the Per-C and are the Per-C output (along with data); so, it is possible for a human to interact with the Per-C using just a vocabulary.

[[File:PerC.jpg|belowframed|center|Figure 1. Architecture for the perceptual computer.]]

A vocabulary is application (context) dependent, and must be large enough so that it lets the end-user interact with the Per-C in a user-friendly manner. The encoder transforms words into [[fuzzy set]]s (FSs) and leads to a ''codebook'' – words with their associated FS models. The outputs of the encoder activate a Computing With Words<ref>Lotfi Zadeh [7], the father of fuzzy logic, coined the phrase computing with words, and stated: ''“CWW is a methodology in which the objects of computation are words and propositions drawn from a natural language. [It is] inspired by the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. CWW may have an important bearing on how humans … make perception-based rational decisions in an environment of imprecision, uncertainty and partial truth.”'' He did not mean that computers would actually compute using words—single words or phrases—rather than numbers. He meant that computers would be activated by words, which would be converted into a mathematical representation using fuzzy sets (FSs), and that these FSs would be mapped by a CWW engine into some other FS, after which the latter would be converted back into a word. Zadeh’s definition of CWW is very general and does not refer to a specific field in which CWW would be used. ''Perceptual computing'' focuses on CWW for making subjective judgments.</ref> (CWW) engine, whose output is one or more other FSs, which are then mapped by the decoder into a recommendation (subjective judgment) with supporting data. The recommendation may be in the form of a word, group of similar words, rank or class.

Although theremany details are lots of details needed in order to implement the Per-C’sC's three components – encoder, decoder and CWW engine – and they are covered in [5], it is when the Per-C is applied to specific applications, that the focus on the methodology becomes clear. Stepping back from those details, the ''methodology of perceptual computing'' is:

# Focus on an application (''A'').

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==Applications of Per-C==

To-date a Per-C has been implemented for the following four applications: (1) investment decision-making, (2) social judgment making, (3) distributed decision making, and (4) hierarchical and distributed decision-making. A specific example of the fourth application is the so-called ''Journal Publication Judgment Advisor'' [5, Ch. 10] in which for the first time only words are used at every level of the following hierarchical and distributed decision making process:

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</blockquote>

How words can be aggregated to reflect each reviewer’sreviewer's recommendation as well as the expertise of each reviewer about the paper’spaper's subject matter is done using a linguistic weighted average. Although the journal publication judgment advisor uses reviewers and an associate editor, the word “reviewer” could be replaced by judge, expert, low-level manager, commander, referee, etc., and the term “associate editor” could be replaced by control center, command center, higher-level manager, etc. So, this application has potential wide applicability to many other applications.

Recently, a new Per-C based [[Failure mode and effects analysis]] (FMEA) methodology was developed, with it'sits application to [[edible bird's nest]] farming, in [[Borneo]], has been reported. <ref> {{cite journal |author1=Chai K.C.|author2=Tay K. M.|author3=Lim C.P. | title=A perceptual computing-based method to prioritize failure modes in failure mode and effect analysis and its application to edible bird nest farming |journal=Applied Soft Computing |volume=49|year=2016|url=http://www.sciencedirect.com/science/article/pii/S1568494616304379 |doi=10.1016/j.asoc.2016.08.043

|pages= 734–747|url=http://ir.unimas.my/13928/7/A%20perceptual%20computing%20%28abstract%29.pdf}}</ref>

[[File:Per-c fmea.png|center|thumb|A Perceptual Computing Based Failure Mode and Effect Analysis Methodology]]

In addition, application of Per-C based method to educational assessment, for [[cooperative learning]] of students has been reported. <ref>{{cite journal |author1=Chai K.C.|author2=Tay K. M.|author3=Lim C.P. | title=A new fuzzy peer assessment methodology for cooperative learning of students |journal=Applied Soft Computing |volume=32|year=2015|doi=10.1016/j.asoc.2015.03.056

|pages= 468-480|url=http://ir.unimas.my/8139/1/A-new-fuzzy.pdf}}</ref>

In summary, the Per-C (whose development has taken more than a decade) is the first complete implementation of Zadeh’sZadeh's CWW paradigm, as applied to assisting people to make subjective judgments.

==See also==

* [[Computing with words and perceptions]]

* [[Computational intelligence]]

* [[Expert system]]

* [[Fuzzy control system]]

* [[Fuzzy logic]]

* [[Fuzzy set]]

* [[Granular computing]]

* [[Rough set]]

* [[Soft computing]]

* [[Type-2 fuzzy sets and systems]]

* [[Vagueness]]

==Footnotes==

{{Reflist}}

<references/>

== References ==

<!--- See [[Wikipedia:Footnotes]] on how to create references using <ref></ref> tags which will then appear here automatically -->

[1] F. Liu and J. M. Mendel, “Encoding words into interval type-2 fuzzy sets using an Interval Approach,” IEEE Trans. on Fuzzy Systems, vol. 16, pp 1503–1521, December 2008.

[2] J. M. Mendel, “The perceptual computer: an architecture for computing with words,” Proc. of Modeling With Words Workshop in the Proc. of FUZZ-IEEE 2001, pp.&nbsp;35–38, Melbourne, Australia, 2001.

[3] J. M. Mendel, “An architecture for making judgments using computing with words,” Int. J. Appl. Math. Comput. Sci., vol. 12, No. 3, pp.&nbsp;325–335, 2002

[4] J. M. Mendel, “Computing with words and its relationships with fuzzistics,” Information Sciences, vol. 177, pp.&nbsp;998–1006, 2007.

[5] J. M. Mendel and D. Wu, Perceptual Computing: Aiding People in Making Subjective Judgments, John Wiley and IEEE Press, 2010.

[6] D.Wu and J. M. Mendel, “Aggregation using the linguistic weighted average and interval type-2 fuzzy sets,” IEEE Trans. on Fuzzy Systems, vol. 15, no. 6, pp.&nbsp;1145–1161, 2007.

== Sources ==

[7] L. A. Zadeh, “Fuzzy logic = computing with words,” IEEE Trans. on Fuzzy Systems, vol. 4, pp.&nbsp;103–111, 1996.

[1]* F. Liu and J. M. Mendel, “Encoding words into interval type-2 fuzzy sets using an Interval Approach,” IEEE Trans. on Fuzzy Systems, vol. 16, pp 1503–1521, December 2008.

[2]* J. M. Mendel, “The perceptual computer: an architecture for computing with words,” Proc. of Modeling With Words Workshop in the Proc. of FUZZ-IEEE 2001, pp.&nbsp;35–38, Melbourne, Australia, 2001.

[3]* J. M. Mendel, “An architecture for making judgments using computing with words,” Int. J. Appl. Math. Comput. Sci., vol. 12, No. 3, pp.&nbsp;325–335, 2002

[4]* J. M. Mendel, “Computing with words and its relationships with fuzzistics,” Information Sciences, vol. 177, pp.&nbsp;998–1006, 2007.

[5]* J. M. Mendel and D. Wu, Perceptual Computing: Aiding People in Making Subjective Judgments, John Wiley and IEEE Press, 2010.

[6]* D.Wu and J. M. Mendel, “Aggregation using the linguistic weighted average and interval type-2 fuzzy sets,” IEEE Trans. on Fuzzy Systems, vol. 15, no. 6, pp.&nbsp;1145–1161, 2007.

[7]* L. A. Zadeh, “Fuzzy logic = computing with words,” IEEE Trans. on Fuzzy Systems, vol. 4, pp.&nbsp;103–111, 1996.

==External links==

* Freeware MATLAB implementations of Per-C are available at: http://sipi.usc.edu/~mendel/software.

[[Category:Artificial intelligence]]

[[Category:Fuzzy logic]]

[[Category:Logic in computer science]]