By Lotfi A. Zadeh

In essence, Computing with phrases (CWW) is a process of computation within which the gadgets of computation are predominantly phrases, words and propositions drawn from a typical language. CWW relies on fuzzy common sense. In technology there's a deep-seated culture of in accordance even more recognize to numbers than to phrases. In a basic means, CWW is a problem to this practice. what's no longer widely known is that, this day, phrases are utilized in position of numbers in a large choice of functions starting from electronic cameras and family home equipment to fraud detection structures, biomedical instrumentation and subway trains.

CWW bargains a different capability—the potential to precisiate normal language. Unprecisiated (raw) usual language can't be computed with. A key proposal which underlies precisiation of that means is that of the that means postulate: A proposition, p, is a restrict at the values which a variable, X—a variable that's implicit in p—is allowed to take.

CWW has a big ramification for arithmetic. Addition of the formalism of CWW to arithmetic empowers arithmetic to build mathematical options of computational difficulties that are said in a average language. conventional arithmetic doesn't have this capability.

**Read Online or Download Computing with Words: Principal Concepts and Ideas PDF**

**Similar intelligence & semantics books**

This ebook constitutes the refereed court cases of the twentieth foreign convention on automatic Deduction, CADE-20, held in Tallinn, Estonia, in July 2005. The 25 revised complete papers and five process descriptions provided have been conscientiously reviewed and chosen from seventy eight submissions. All present facets of automatic deduction are addressed, starting from theoretical and methodological concerns to presentation and assessment of theorem provers and logical reasoning platforms.

**New Concepts and Applications in Soft Computing**

The ebook presents a pattern of analysis at the cutting edge idea and functions of soppy computing paradigms. the assumption of soppy Computing used to be initiated in 1981 whilst Professor Zadeh released his first paper on delicate information research and always developed ever when you consider that. Professor Zadeh outlined gentle Computing because the fusion of the fields of fuzzy good judgment (FL), neural community thought (NN) and probabilistic reasoning (PR), with the latter subsuming trust networks, evolutionary computing together with DNA computing, chaos idea and elements of studying concept into one multidisciplinary approach.

**Logic programming and non-monotonic reasoning : proceedings of the second international workshop**

This can be the second one in a sequence of workshops which are bringing jointly researchers from the theoretical finish of either the common sense programming and synthetic intelligence groups to debate their mutual pursuits. This workshop emphasizes the connection among common sense programming and non-monotonic reasoning.

**Handbook of Metadata, Semantics and Ontologies**

Metadata examine has emerged as a self-discipline cross-cutting many domain names, involved in the availability of allotted descriptions (often referred to as annotations) to net assets or functions. Such linked descriptions are meant to function a beginning for complicated providers in lots of program components, together with seek and site, personalization, federation of repositories and automatic supply of data.

- The Turing Test and the Frame Problem: Ai's Mistaken Understanding of Intelligence (Ablex Series in Artificial Intelligence)
- Shape Understanding System – Knowledge Implementation and Learning
- Translation and Web Searching
- Fuzzy Systems Engineering: Toward Human-Centric Computing
- Generating Natural Language Under Pragmatic Constraints
- Introduction to Artificial Intelligence

**Additional info for Computing with Words: Principal Concepts and Ideas**

**Sample text**

RATIONALES FOR THE USE OF WORDS use of words A B C necessary advantageous expedient Numbers not known Numbers are known. There is a tolerance for imprecision. Words are good enough. Linguistic summarization 42/263 NOTE z Today, most applications of CWW1, especially in the realm of consumer products, are based on Rationales B and C. A key role is played by linguistic summarization. 43/263 23 24 What Is Computing with Words (CWW)? LINGUISTIC SUMMARIZATION VIA GRANULATION (FUZZY PARTITION) Y f granule L granulation M S 0 0 X Y S medium × large (M×L) *f (fuzzy graph) M L (large) granulation fsummarization*f : if X is small then Y is small *f = if X is medium then Y is large if X is large then Y is small X 0 (For definition of granulation see Slide 94) 44/263 FUZZY LOGIC GAMBIT z Fuzzy Logic Gambit = deliberate imprecisiation through granulation, followed by graduation Y f granulation if X is small then Y is small if X is medium then Y is large summarization if X is large then Y is small 0 z X The Fuzzy Logic Gambit is employed in many applications of fuzzy logic, especially in the realm of consumer products 45/263 What Is Computing with Words (CWW)?

52/263 COMMENT (Kalman 1972) I would like to comment briefly on Professor Zadeh’s presentation. His proposals could be severely, ferociously, even brutally criticized from a technical point of view. This would be out of place here. But a blunt question remains: Is Professor Zadeh presenting important ideas or is he indulging in wishful thinking? 53/263 What Is Computing with Words (CWW)? The most serious objection to fuzzification of system analysis is that lack of methods of system analysis is not the principal scientific problem in the systems field.

RATIONALES FOR THE USE OF WORDS use of words A B C necessary advantageous expedient Numbers not known Numbers are known. There is a tolerance for imprecision. Words are good enough. Linguistic summarization 42/263 NOTE z Today, most applications of CWW1, especially in the realm of consumer products, are based on Rationales B and C. A key role is played by linguistic summarization. 43/263 23 24 What Is Computing with Words (CWW)? LINGUISTIC SUMMARIZATION VIA GRANULATION (FUZZY PARTITION) Y f granule L granulation M S 0 0 X Y S medium × large (M×L) *f (fuzzy graph) M L (large) granulation fsummarization*f : if X is small then Y is small *f = if X is medium then Y is large if X is large then Y is small X 0 (For definition of granulation see Slide 94) 44/263 FUZZY LOGIC GAMBIT z Fuzzy Logic Gambit = deliberate imprecisiation through granulation, followed by graduation Y f granulation if X is small then Y is small if X is medium then Y is large summarization if X is large then Y is small 0 z X The Fuzzy Logic Gambit is employed in many applications of fuzzy logic, especially in the realm of consumer products 45/263 What Is Computing with Words (CWW)?