1.

Seising R.: The Fuzzification of Systems. The Genesis of Fuzzy Set Theory and Its Initial ApplicationsDevelopments up to the 1970s. Springer, Berlin (2007). A history of Fuzzy Set Theory and the ways it was first used. The book incorporates this genesis of the new theory into the history of 20th century science and technology. Influences from philosophy, system theory and cybernetics stemming from the earliest part of the 20th century are considered alongside those of communication and control theory from mid-century

2.

Zadeh, L.A., Desoer, C.A.: Linear System Theory: The State Space Approach. McGraw-Hill, New York (1963). This textbook for engineers in research and development and applied mathematicians is landmark in the development of the state space approach. It concerns the technique’s application to systems described by differential equations

3.

Zadeh, L.A., Polak, E.: System Theory, Bombay. McGraw-Hill, New Delhi (1969). This vol. 8 in the Inter-University electronics series is a collection of papers on system theory

4.

Zadeh L.A.: The Concept of State in System Theory, in [3, p. 9–42]. In this book chapter Zadeh presented the “state space approach” to System Theory

5.

Zadeh L.A.: System theory. Columbia Eng. Q., 16–19, 34 (1954). Zadeh’s first paper on System theory in the New York student publication Columbia Engineering Quarterly

6.

Zadeh, L.A.: Some basic problems in communication of information. New York Acad. Sci. Series II
14(5), 201–204 (1952). Zadeh’s talk at the meeting of the Section of Mathematics and Engineering of the New York Academy of Sciences on February 15, 1952

7.

Zadeh, L.A., Miller, K.S.: Generalized ideal filters. J. Appl. Phys.

23(2), 223–228 (1952). In this paper the authors established their general theory of linear signal transmission systems with extensive use of modern mathematical methods: Fourier analysis as well as Hilbert space and operator calculus

CrossRefMATHMathSciNet
8.

Zadeh, L.A.: Theory of filtering. J. Soc. Ind. Appl. Math.

1, 35–51 (1953). In this article on his general filter theory Zadeh emphasized a distinction between ideal and optimum filters. The former are defined as filters which achieve a perfect separation of signal and noise, but if ideal filtration is not possible, though, which is often the case when the signal is mixed with noise, then one must accept that the filtration can only be incomplete. In such cases, a filter that delivers the best possible approximation of the desired signal and “a particular meaning” of “best approximation” is used here – is called an optimum filter

CrossRefMATHMathSciNet
9.

Zadeh, L.A.: From circuit theory to system theory. Proc. IRE

50, 856–865 (1962). This article was written for the anniversary edition of the Proceedings of the IRE appeared in May 1962 to mark the 50th year of the Institute of Radio Engineers (IRE). The article presents a brief survey of the evolution of system theory, together with an exposition of some of its main concepts, techniques and problems. It concerns problems and applications of system theory and its relations to network theory, control theory, and information theory. The discussion is centered on the notion of state and emphasizes the role played by state-space techniques

CrossRefMathSciNet
10.

Bellman, R.E: Dynamic Programming. Princeton University Press, Princeton (1957). This is Bellman’s introduction to the mathematical theory of multistage decision processes. Dynamic programming describes the process of solving problems where one needs to find the best decisions one after another

11.

Zadeh, L.A.: Fuzzy sets and systems. In: Fox, J. (ed.) System Theory. Microwave Research Institute Symposia Series XV, pp. 29–37. Polytechnic Press, Brooklyn, New York (1965). Zadeh’s contribution in the proceedings of the Symposium on System Theory (April 20-22, 1965) at the Polytechnic Institute in Brooklyn, When Zadeh gave this talk it was entitled “A New View on System Theory”

12.

Zadeh, L.A.: Fuzzy sets. Inf. Control

8, 338–353 (1965). This is the first and seminal article on fuzzy sets

CrossRefMATHMathSciNet
13.

Zadeh, L.A.: Fuzzy sets. ERL Report no. 64–44, University of California at Berkeley, 16 Nov 1964. Zadeh’s preprint of the article [12]

14.

Bellman R.E., Kalaba, R.E., Zadeh L.A.: J. Math. Anal. Appl.
13, 1–7 (1966). This article was published in 1966 but its text did appear already as a RAND memorandum two years before: see [15]

15.

Bellman R.E., Kalaba, R.E., Zadeh L.A: Abstraction and Pattern Classification. Memorandum RM-4307-PR, Santa Monica, California: The RAND Corporation, October 1964. Zadeh’s first paper on fuzzy sets and pattern recognition problems that appeared at first as a RAND-Corporation memorandum in. Even this paper has three co-authors it was written by Lotfi Zadeh. It contains the first definitions of the theory of fuzzy sets in a scientific text. Two years later this paper appeared under the same title and authorship as a journal article, see [14]

16.

Zadeh, L.A.: Towards a theory of fuzzy systems. In: Kalman R.E., DeClaris N. (eds.) Aspects of Network and System Theory, pp. 469–490. Holt, Rinehart and Winston, New York (1971). Zadeh’s contribution to an anthology on Network and System Theory

17.

Black, M.: Vagueness. An exercise in logical analysis. Philos. Sci.

4, 427–455 (1937). In this article the philosopher Max Black analyzed the nature of vagueness and the significance this concept might have for logic

CrossRef
18.

Black, M.: Letter to Lotfi A. Zadeh at June 21, 1967. Private Archives of Lotfi A. Zadeh

19.

Black, M.: Language and Philosophy. Cornell University Press, Ithaca (1949). This book is a collection of Black’s articles on several topics in philosophy of language, semantics, and semiotics. It also contents his article [17]

20.

Black, M.: Reasoning with loose concepts. Dialogue

2(1), 1–12 (1963). This is Black’s second paper on vague (or loose) concepts; for his first article see [17]. Here he said that classical logic is only applicable in a tentative, rough and ready way to our terrestrial world

CrossRef
21.

Kant, I.: Kritik der reinen Vernunft. Meiner Verlag, Hamburg, [1781] (1998). One of the most influential books in the history of philosophy, English Title: Critique of Pure Reason. “I do not mean by this a critique of books and systems, but of the faculty of reason in general, in respect of all knowledge after which it may strive independently of all experience.” (Preface to the first edition.)

22.

Hertz, H.: Die Prinzipien der Mechanik in neuen Zusammenhange dargestellt. Drei Beiträge, Ostwalds Klassiker der exakten Wissenschaften, Bd. 263) (1894), new ed.: Frankfurt am Main: Verlag Harri Deutsch 1996), Hertz’s posthumously published approach to mechanics with a philosophical introduction anticipated current discussions on the role of models in science. English translation: The Principles of Mechanics Presented in a New Form. Dover, New York (1956)

23.

Wittgenstein, L.: Tractatus logico-philosophicus. Routledge & Kegan Paul, London. (First in German: L. Wittgenstein: Logisch-Philosophische Abhandlung. Ostwalds Annalen der Naturphilosophie, Band 14, Leipzig (1921). Wittgenstein’s first book concerns the philosophical problems which deal with the world, thought and language. Wittgenstein’s “solution” bases in logic and in the nature of representation

24.

Wittgenstein, L.: Werkausgabe in acht Bänden (1914–1916), new ed.: Frankfurt am Main: Suhrkamp, Bd. 8, 1984. This is the German edition of Wittgenstein’s Collected Works

25.

Kortabinśki, T.: Elementy teorii poznania, logiki formalnej i metodologii nauk. Lwów, Ossolineum (1929). In this book (English translation: “Gnosiology”, 1966) the Polish philosopher Kortabinśki argued that a concept for a property is vague if the property may be the case by grades

26.

Ajdukiewicz, K.: On the problem of universals. Prz. Filozof.
38(1935), 219–234 (1935). In this article the Polish philosopher Ajdukiewicz argued that “a term is vague if and only if its use in a decidable context [..] will make the context undecidable in virtue of those [language] rules”

27.

Frege, G.: Begriffsschrift, eine der arithmetischen nachgebildete Formelsprache des reinen Denkens, Halle (1879). This book (English Title: Concept-Script presents A Formal Language for Pure Thought Modeled on that of Arithmetic (subtitle) as a second-order predicate calculus. This is used to define mathematical concepts and to state and prove mathematically propositions

28.

Frege, G.: Funktion und Begriff. In: Frege, G. Funktion, Begriff, Bedeutung (ed.: Patzig G.). Vandenheoeck & Ruprecht, Gttingen, 1986, 1839 (1891). In this philosophical article, English title “On Function and Concept”, Frege defines a concept as a monadic function whose value is always a truth value

29.

Frege, G.: Grundgesetze der Arithmetik, vol. 2, Hermann Pohle, Jena (1893–1903). In this book, engl. title: The Foundations of Arithmetic: A Logic-Mathematical Enquiry into the Concept of Number, Frege attempted to derive, by use of his symbolism, all of the laws of arithmetic from axioms he asserted as logical. Most of these axioms were carried over from his Begriffsschrift [27]

30.

Russell, B.: Vagueness. Aust. J. Psychol. Philos.
1, 84–92 (1923). In this article the mathematician and philosopher Bertrand Russell discusses some of the most important problems concerning the nature of vagueness, its extension within the language, and its relation to truth and logic

31.

Menger, K.: Statistical metrics. Proc. Natl. Acad. Sci. USA
28, 535–537 (1942). In this short paper Menger introduced his extension of the concept of a metrics to statistical metrics

32.

Menger, K.: Probabilistic geometry. Proc. Natl. Acad. Sci. USA

37, 226–229 (1951). In this short paper Menger used his concept of statistical metrics in geometry

CrossRefMATHMathSciNet
33.

Menger, K.: Probabilistic theories of relations. Proc. Natl. Acad. Sci. USA
37, 178180 (1951). In this short paper Menger introduced the concept of probabilistic relations

34.

Menger, K.: Ensembles flous et fonctions aléatoires. Comptes Rendus Académie des Sciences

37, 226–229 (1951). In this paper that was written by Menger when he was a visiting professor in Paris, he introduced the concept of “ensembles fluos” or “hazy sets”. Today “ensembles flous” are the French name for fuzzy sets but Menger’s old concept of “ensembles flous” was still probabilistic and not identical with fuzzy sets

MATHMathSciNet
35.

Menger, K.: Mathematical implications of Mach’s ideas: positivistic geometry, the clarification of functional connections. In: Cohen, R.S., Seeger, R.J. (eds.) Ernst Mach, Physicist and Philosopher, Boston Studies in the Philosophy of Science, vol. 6. Reidel, Dordrecht, pp. 107–125 (1970). Reprint as: Menger K. Geometry and Positivism. A Probabilistic Microgeometry. In: Menger K. Selected Papers in Logic and Foundations, Didactics, Economics. Dordrecht: D. Reidel Publ. Comp., 225–234 (1979). Citation after the reprinted version. This article is the printed form of Menger’s contribution to the symposium of the American Association for the Advancement of Science, organized in 1966 to commemorate the 50th anniversary of Ernst Machs death. In this contribution he compared his “microgeometry” or “probabilistic geometry” (see [32]) with the theory of fuzzy sets. However, he mentioned the difference between his concept of hazy sets and Zadeh’s concept of fuzzy sets because he wrote that Zadeh spoke “of the degree rather than the probability of an element belonging to a set”

36.

Wittgenstein, L.: Philosophical Investigations. Blackwell Publishing, Oxford (1953). In his second book, published posthumously, Wittgenstein discusses several philosophical problems. On the contrary to his Tractatus Logico-Philosophicus he claimed that most philosophical problems root in conceptual confusions surrounding language use

37.

Goguen, J.A.:

\(L\)-fuzzy sets. J. Math. Anal. Appl.

18, 145–174 (1967). This is Goguens first article on his generalization of fuzzy sets to “

\(L\)-sets”; see also [38]

CrossRefMATHMathSciNet
38.

Goguen, J.A.: Categories of Fuzzy Sets: Applications of a Non-Cantorian Set Theory. University of California at Berkeley, Ph. D. Diss. Dept (1968). This is Goguen’s Ph. D. thesis. He generalized fuzzy sets to “
\(L\)-sets”. An
\(L\)-set is a function that maps the fuzzy set carrier
\(X\) into a partially ordered set
\(L\);
\(X \rightarrow L\)

39.

Goguen, J.A.: The logic of inexact concepts. Synthese

19, 325–373 (1969). In this article Goguen interpreted the elements of

\(L\) as “truth values”

CrossRefMATH
40.

Zadeh, L.A.: Fuzzy Languages and their Relation to Human and Machine Intelligence. In: Man and Computer. Proceedings of the International Conference Bordeaux 1970, Karger: Basel, pp. 13–165 (1970). In this proceedings paper Zadeh’s thesis was that the difference between human and mechanical intelligence lay in the ability of the human brain “an ability which present-day digital computers do not possess—to think and reason in imprecise, non-quantitative terms”. He said that humans could understand inexact instructions, whereas inputs for a computer had to be defined with precision. He suggested devising fuzzy languages which functioned such that commands formulated in a language like this could also be processed and carried out by future computers

41.

Wee, W.G.: On a Generalization of Adaptive Algorithms and Applications of the Fuzzy Set Concept to Pattern Classification. Ph.D Thesis, Purdue University, Technical Report, vol. 67, issue no 7 (1967). In his Ph D dissertation, written this work under King Sun Fu, Wee had applied the fuzzy sets to iterative learning procedures for pattern classification and he had defined a finite automaton based on Zadehs concept of the fuzzy relation as a model for learning systems

42.

Wee, W.G., Fu, K.S.: A formulation of fuzzy automata and its application as a model of learning systems. IEEE T. Syst. Sci. Cyb. SSC-

5(3), 215–223 (1969)

CrossRefMATH
43.

Zadeh, L.A.: Fuzzy algorithms. Inf. Control

12, 99–102 (1968). In this article Zadeh introduced the concept of fuzzy algorithms

CrossRefMathSciNet
44.

Zadeh L.A.: Toward fuzziness in computer systems. Fuzzy Algorithms and Languages. In: Boulaye, G.G. (ed.) Structure et Conception des Ordiinateures - Architecture and Design of Digital Computers, École d’été de l’O.T.A.N., A N. A. T. O, pp. 9–18. Advanced Summer Institute, Dunod, Paris (1969). In this contribution to a NATO summer school Zadeh gave a view on his expectations on fuzziness in the area of computers

45.

Turakainen, P.: On stochastic languages. Inf. Control

12(4), 304–313 (1968). This article presents a concept of stochastic languages as an approximation to human languages using randomizations in the productions

CrossRefMATHMathSciNet
46.

Lee, E.T., Zadeh, L.A.: Note on fuzzy languages. Inf. Sci.

1, 421–434 (1969). In this short paper Zadeh and his Ph D student Lee present their program to extend non-fuzzy formal languages to fuzzy languages

CrossRefMathSciNet
47.

Hopcroft, J.E., Ullman J.D.: Formal Languages and their Relation to Automata. Addison Wesley, Reading (1969). This is the authors’ seminal study of formal languages that constituted an important subarea of computer science

48.

Zadeh, L.A.: Similarity relations and fuzzy orderings. Inf. Sci.

3, 177–200 (1971). In this article Zadeh defined similarity relations as a generalization of the concept of equivalence relations (reflexive symmetrical and transitive) and fuzzy orderings as transitive fuzzy relations

CrossRefMATHMathSciNet
49.

Zadeh, L.A.: Quantitative fuzzy semantics. Inf. Sci.

3, 159–176 (1971). In this article Zadeh defined a language as a fuzzy relation between a set of terms

\(T = {x}\) and the universe of discourse

\(U = {y}\). If a term

\(x\) of

\(T\) is given, then the membership function

\(_L (x, y)\) defines a set

\(M(x)\) in

\(U\) with membership function:

\(_{Mx} (y) = _L (x, y)\). Zadeh called the fuzzy set

\(M(x)\) the meaning of the term

\(x\);

\(x\) is thus the name of

\(M(x)\)
CrossRefMATHMathSciNet
50.

Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE T. Syst. Man Cyb. SMC-

3(1), 28–44 (1973). In this article Zadeh treated fuzzy algorithms and he also integrated the other fuzzifications into a new approach that was supposed to bring about a completely new form of system analysis based on his Fuzzy Set Theory by using Linguistic Variables, Fuzzy If-Then-rules, and Fuzzy Algorithms

CrossRefMATHMathSciNet
51.

Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning—I. Inf. Sci.
8, 199–249;—II, Inf. Sci.
8, 301–357;—III, Inf. Sci.
9, 43–80 (1975). In this series of three articles Zadeh introduces his linguistic approach to Approximate Reasoning: By linguistic variables as variables whose values are words or sentences in a natural or artificial language. He expected that the main applications of the linguistic approach lie in the realm of humanistic systems, particularly in the fields of artificial intelligence, linguistics, human decision processes, pattern recognition, psychology, law, medical diagnosis, information retrieval, economics and related areas

52.

Zadeh, L.A.: Fuzzy logic and approximate reasoning. Synthese

30, 407–428 (1975). Zadeh’s article on the imprecise logical system, FL, in a philosophical journal. In FL the truth-values are fuzzy sets of the unit interval with linguistic labels such as true, false but also not true, very true, quite true, not very true and not very false, etc

CrossRefMATH
53.

Zadeh, L.A.: PRUF a meaning representation language for natural languages. Int. J. Man Mach. Stud.

10, 395–460 (1978). In this article Zadeh describes the relation-manipulating language Probabilistic Relational Universal Fuzzy (PRUF), to precisiate expressions in a natural language; to exhibit their logical structure; and to provide a system for the characterization of the meaning of a proposition by acting on a collection of fuzzy relations in a data base and returning a possibility distribution

CrossRefMATHMathSciNet
54.

Rosch, E.: Natural categories. Cogn. Psychol.

4, 328–350 (1973). In this article the psychologist Eleanor Rosch demonstrated—based on a series of experiments in the 1970s—that when people label an object, they rely on a comparison with what they regard as a prototype of the category designated by that word but less on abstract definitions

CrossRef
55.

Lakoff, G.: Hedges. A study in meaning criteria and the logic of fuzzy concepts. J. Philos. Logic
2, 458–508 (1973). Influenced by Rosch and Zadeh the linguist Lakoff employed in this paper “hedges” (meaning barriers) to categorize linguistic expressions. He also introduced in this article the term “fuzzy logic”

56.

Zadeh, L.A.: A fuzzy-set-theoretic interpretation of linguistic hedges. J. Cybern.

2, 4–34 (1972). Zadeh’s article on “linguistic operators”—e.g. very, more, more or less, much, essentially, slightly etc., which he called “hedges”

CrossRefMathSciNet
57.

Zadeh, L.A.: Interview with Lotfi Zadeh, creator of fuzzy logic by Betty Blair. Azerbaijada Int.
2(4) (1994). An interesting interview on the history and the future of Fuzzy Sets and Systems with the founder of this theory

58.

Seising, R., Sanz, V. (eds.): Soft Computing in Humanities and Social Sciences. Springer, Berlin (2012). This anthology presents a generous sampling of a wide array of authors and subject matters from different disciplines. Some of the contributors of the book belong to the scientific and technical areas of Soft Computing while others come from various fields in the humanities and social sciences such as Philosophy, History, Sociology or Economics

59.

Seising, R.: The Experimenter and the Theoretician - Linguistic Synthesis to tell Machines what to do. In: Trillas, E., Bonissone, P., Magdalena, L., Kacprycz, J. (eds.) Combining Experimentation and Theory—A Homage to Abe Mamdani, pp. 329–358. Springer, Berlin (2012). This book contribution concerns the life work of two pioneers of Fuzzy Sets and Systems, Ebrahim H. Mamdani and Lotfi A. Zadeh. Mamdani initiated the development of practical Fuzzy Control systems whereas Zadeh founded the theory of this field. When they have been asked to characterize their own role in science, the former characterized himself less close to mathematics than the other

CrossRef
60.

Mamdani, E.H.: Advances in the linguistic synthesis of fuzzy controllers. Int. J. Man Mach. Stud.

8, 669–678 (1976). An article by Mamdani’s on the method of fuzzy control using the example of the steam engine

CrossRefMATH
61.

Mamdani, E.H.: How a mouse crossed scientists mind a conversation with Ebrahim Mamdani. JAMRIS
2(1), 74–76 (2008). An interesting interview on Mamdani’s view on science and particular on Artificial Intelligence

62.

Assilian, S.: Artificial intelligence in the control of real dynamic systems. Ph. D. Thesis Nr. DX193553, University London (1974). Assilian’s Ph D Dissertation thesis on the first fuzzy control system

63.

Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud.

7(1), 1–13 (1975). The article on the fuzzy controlled steam engine written by Mamdani and Asilian

CrossRefMATH
64.

McNeill, D., Freiberger, P.: Fuzzy Logic. Simon and Schuster, New York (1993). A book on the history of fuzzy sets written by two journalists

65.

Tong, R.M.: An Assessment of a Fuzzy Control Algorithm for a Nonlinear Multivariable system. In: Proceedings of the Workshop on Discrete Systems and fuzzy Reasoning. Queen Mary College, London (1976). This paper presents an early fuzzy control application system of in a basic oxygen steel making process in England

66.

Rutherford, D.A.: The Implementation and Evaluation of a Fuzzy Control Algorithmus for a Sinter Plant. In: Mamdani, E.H., Gaines, B.R. (eds.) Discrete Systems and Fuzzy Reasoning, EES-MMS-DSFR-76. Proceedings of the Workshop Queen Mary College, London (1976). This paper presents an early fuzzy control application system of a sinter making plant in England

67.

Carter, A., Hague, M.J.: Fuzzy control of raw mix permeability at a sinter plant. In: Mamdani, E.H., Gaines, B.R. (eds.) Discrete Systems and Fuzzy Reasoning, EES-MMSDSFR-76. Proceedings of the Workshop held at Queen Mary College, University of London (1976). This is a presentation of a fuzzy controlled sinter making plant in England, see [66]

68.

Kickert, W.J.M.: Analysis of a Fuzzy Logic Controller. Internal Report Queen Mary College, London (1976). This paper presents a fuzzy controlled pilot scale batch chemical process in England

69.

King, P.J., Mamdani, E.H.: The Application of Fuzzy Control Systems to Industrial Processes. In: Mamdani, E.H., Gaines, B.R. (eds.) Discrete Systems and Fuzzy Reasoning, EES-MMS-DSFR-76. Proceedings of the Workshop held at Queen Mary College, University of London, (1976). This paper presents another aspect of the fuzzy control system in [68]

70.

Kickert, W.J.M., van Nautka Lemke H.R.: Application of fuzzy controller in a warm water plant. Automatica
12, 301–308 (1976). This paper deals with a fuzzy control system to control a warm water plant in the Netherlands

71.

Holmblad, L.P., Østergaard, J.J.: Control of a cement Kiln by fuzzy logic. In: Gupta, M.M., Ragade, M.R.K., Yager, R.R. (eds.) Advances in Fuzzy Set Theory and Applications. North-Holland Publishing Company, Amsterdam, New York, Oxford (1979). This article describes the first a commercial fuzzy control system for the automatic control of a cement kiln in Danmark

72.

Zadeh, L.A.: Biological Application of the Theory of Fuzzy Sets and Systems. In: Proctor, L.D. (ed.).: Proc. International Symposium on Biocybernetics of the Central Nervous System, pp. 199–206. Little, Brown and Comp., London (1969). Zadehs conference paper to advise life scientists to use fuzzy set theory

73.

Seising, R., Sanz, V.: Introduction. In: [58], 3–36 (2012). This introduction to the volume [58] illuminates the relations between hard and soft sciences and hard and soft computing with each other

74.

Seising, R., Sanz, V.: (guest eds.). Soft computing in humanities and social sciences, special issue. Fuzzy Sets Syst.
214, 1–96 (2013). This special issue of the journal concerns theoretical research and practical applications of Fuzzy Sets and Systems in non-technical fields

75.

Zadeh, L.A.: Making computers think like people. IEEE Spectr.

8, 26–32 (1984). In this article Zadeh focused on the machines ability to “compute with numbers” that he intends to supplement by an additional ability that is similar to human thinking. The “remarkable human capability [of humans] to perform a wide variety of physical and mental tasks without any measurements and any computations.”

CrossRef
76.

Zadeh, L.A.: Fuzzy logic = computing with words. IEEE T. Fuzzy Syst.

4(2), 103–111 (1996). Computing with Words (CW) is introduced in this article as a methodology in which words are used in place of numbers for computing and reasoning. In CW, a word is viewed as a label of a fuzzy set of points drawn together by similarity, with the fuzzy set playing the role of a fuzzy constraint on a variable

CrossRefMathSciNet
77.

Zadeh, L.A.: From computing with numbers to computing with words - from manipulation of measurements to manipulation of perceptions. IEEE T Circuits Syst.-I: Fundam. Theory Appl.
45(1), 105–119 (1999). In this article Zadeh proposed Computing with Words (CW) based on the theories of Fuzzy Sets and Systems and Fuzzy Logic and these methodologies instead of exact Computing with numbers. In this article he wrote that “the main contribution of fuzzy logic is a methodology for computing with words. No other methodology serves this purpose.”

78.

Zadeh, L.A.: New Direction in AI. Toward a computational theory of perceptions. AI Mag.
22(1), 73–84 (2001). In this article Zadeh outlines the Computational Theory of Perceptions (CTP). CTP as a new direction in AI is intended to be a capability to compute and reason with perception-based information. Perceptions would be described by propositions drawn from a natural language