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Issue:From 0,1-based logic to interval logic: Difference between revisions

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{{issue/author
{{issue/author
  | author          = Hung Nguyen
  | author          = Hung Nguyen
  | institution    =  
  | institution    = Department of Mathematical Sciences, New Mexico State University
  | address        =  
  | address        = Las Cruces, NM 88003, USA
  | email-before-at =  
  | email-before-at = hunguyen
  | email-after-at  =  
  | email-after-at  = nmsu.edu
}}
}}
{{issue/author
{{issue/author
  | author          = Vladik Kreinovich
  | author          = Vladik Kreinovich
  | institution    =  
  | institution    = Department of Computer Science, University of Texas at El Paso
  | address        =  
  | address        = El Paso, TX
  | email-before-at =  
  | email-before-at = vladik
  | email-after-at  =  
  | email-after-at  = cs.utep.edu
}}
}}
{{issue/data
{{issue/data
  | conference      = 6<sup>th</sup> [[ICIFS]], Varna, 13—14 Sept 2002
  | conference      = 6<sup>th</sup> [[ICIFS]], Varna, 13—14 Sept 2002
  | issue          = Conference proceedings, [[Notes on Intuitionistic Fuzzy Sets/08/3|"Notes on IFS", Volume 8 (2002) Number 3]], pages 75—94
  | issue          = [[Notes on Intuitionistic Fuzzy Sets/08/3|"Notes on Intuitionistic Fuzzy Sets", Volume 8 (2002) Number 3]], pages 75—94
  | file            = NIFS-08-3-075-094.pdf
  | file            = NIFS-08-3-075-094.pdf
  | format          = PDF
  | format          = PDF
  | size            =  
  | size            = 199
  | abstract        =  
  | abstract        =  
Since early 1960s, we have a complete description of all possible [0,1]-based logical operations, namely of "and"-operations (t-norms) and of "or"-operations (t-conorms). In some real-life situations, intervals provide a more adequate way of describing uncertainty, so we need to describe interval-based logical operations ([[intuitionistic fuzzy logic]] can be viewed as an equivalent form of [[interval-valued fuzzy logic]]). Usually, researchers followed a pragmatic path and simply derived these operations from the [0,1]-based ones. From the foundational viewpoint, it is desirable not to a priori restrict ourselves to such derivative operations but, instead, to get a description of all interval-based operations which satisfy reasonable properties.  
Since early 1960s, we have a complete description of all possible [0,1]-based logical operations, namely of "and"-operations (t-norms) and of "or"-operations (t-conorms). In some real-life situations, intervals provide a more adequate way of describing uncertainty, so we need to describe interval-based logical operations ([[intuitionistic fuzzy logic]] can be viewed as an equivalent form of [[interval-valued fuzzy logic]]). Usually, researchers followed a pragmatic path and simply derived these operations from the [0,1]-based ones. From the foundational viewpoint, it is desirable not to a priori restrict ourselves to such derivative operations but, instead, to get a description of all interval-based operations which satisfy reasonable properties.  
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# R. B. Kearfott, Rigorous global search: continuous problems, Kluwer, Dordrecht, 1996.
# R. B. Kearfott, Rigorous global search: continuous problems, Kluwer, Dordrecht, 1996.
# R. B. Kearfott and V. Kreinovich (eds.), Applications of Interval Computations, Kluwer, Dordrecht, 1996.
# R. B. Kearfott and V. Kreinovich (eds.), Applications of Interval Computations, Kluwer, Dordrecht, 1996.
# G. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, Upper Saddle River, New Jersey, 1995.
# [[George Klir|G. Klir]] and [[Bo Yuan|B. Yuan]], Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, Upper Saddle River, New Jersey, 1995.
# V. Kreinovich, G. C. Mouzouris, and H. T. Nguyen, "Fuzzy rule based modeling as a universal control tool", In: H. T. Nguyen and M. Sugeno (eds.), Fuzzy Systems: Modeling and Control, Kluwer, Boston, Massachusetts, 1998, pp. 135-195.
# V. Kreinovich, G. C. Mouzouris, and H. T. Nguyen, "Fuzzy rule based modeling as a universal control tool", In: H. T. Nguyen and M. Sugeno (eds.), Fuzzy Systems: Modeling and Control, Kluwer, Boston, Massachusetts, 1998, pp. 135-195.
# C. H. Ling, "Representation of associative functions", Publ. Math. Debrecen, 1965, Vol. 12, pp. 189-212.
# C. H. Ling, "Representation of associative functions", Publ. Math. Debrecen, 1965, Vol. 12, pp. 189-212.
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# H. Ratschek and J. Rokne, New computer methods for global optimization, Ellis Horwood, Chichester, 1988.
# H. Ratschek and J. Rokne, New computer methods for global optimization, Ellis Horwood, Chichester, 1988.
# B. Schweizer and A. Sklar, Probabilistic metric spaces, North Holland, New York, 1983.
# B. Schweizer and A. Sklar, Probabilistic metric spaces, North Holland, New York, 1983.
# M. H. Smith and V. Kreinovich, "Optimal strategy of switching reasoning methods in fuzzy control", In: H. T. Nguyen, M. Sugeno, R. Tong, and R. Yager (eds.), Theoretical aspects of fuzzy control, J. Wiley, New York, 1995, pp. 117-146.
# M. H. Smith and V. Kreinovich, "Optimal strategy of switching reasoning methods in fuzzy control", In: H. T. Nguyen, M. Sugeno, R. Tong, and [[Ronald Yager|R. Yager]] (eds.), Theoretical aspects of fuzzy control, J. Wiley, New York, 1995, pp. 117-146.
# E. Tsang, Foundations of Constraint Satisfaction, Academic Press, N.Y., 1993.  
# E. Tsang, Foundations of Constraint Satisfaction, Academic Press, N.Y., 1993.  
# I. B. Türkşen, "Interval valued fuzzy sets based on normal forms", Fuzzy Sets and Systems, 1986, Vol. 20, pp. 191-210.
# I. B. Türkşen, "Interval valued fuzzy sets based on normal forms", Fuzzy Sets and Systems, 1986, Vol. 20, pp. 191-210.
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# P. Van Hentenryck, L. Michel, and Y. Deville, Numerica: A Modeling Language for Global Optimization, MIT Press, Cambridge, Massachusetts, 1997.
# P. Van Hentenryck, L. Michel, and Y. Deville, Numerica: A Modeling Language for Global Optimization, MIT Press, Cambridge, Massachusetts, 1997.
# C. Walker and E. A. Walker, private communication, 1995.
# C. Walker and E. A. Walker, private communication, 1995.
# L. A. Zadeh, "Fuzzy Sets", Information and Control, 1965, Vol. 8, pp. 338-353.
# [[Lotfi Zadeh|L. A. Zadeh]], "Fuzzy Sets", Information and Control, 1965, Vol. 8, pp. 338-353.
# Q. Zuo, "Description of strictly monotonic interval AND/OR operations", Reliable Computing, 1995, Supplement (Extended Abstracts of APIC'95: International Workshop on Applications of Interval Computations, El Paso, TX, Febr. 23{25, 1995), pp. 232-235.
# Q. Zuo, "Description of strictly monotonic interval AND/OR operations", Reliable Computing, 1995, Supplement (Extended Abstracts of APIC'95: International Workshop on Applications of Interval Computations, El Paso, TX, Febr. 23{25, 1995), pp. 232-235.



Latest revision as of 13:00, 13 August 2024

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http://ifigenia.org/wiki/issue:nifs/8/3/75-94
Title of paper: From [0,1]-based logic to interval logic
Author(s):
Hung Nguyen
Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM 88003, USA
hunguyen@nmsu.edu
Vladik Kreinovich
Department of Computer Science, University of Texas at El Paso, El Paso, TX
vladik@cs.utep.edu
Presented at: 6th ICIFS, Varna, 13—14 Sept 2002
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 8 (2002) Number 3, pages 75—94
Download:  PDF (199  Kb, File info)
Abstract: Since early 1960s, we have a complete description of all possible [0,1]-based logical operations, namely of "and"-operations (t-norms) and of "or"-operations (t-conorms). In some real-life situations, intervals provide a more adequate way of describing uncertainty, so we need to describe interval-based logical operations (intuitionistic fuzzy logic can be viewed as an equivalent form of interval-valued fuzzy logic). Usually, researchers followed a pragmatic path and simply derived these operations from the [0,1]-based ones. From the foundational viewpoint, it is desirable not to a priori restrict ourselves to such derivative operations but, instead, to get a description of all interval-based operations which satisfy reasonable properties.

Such description is presented in this paper. It turns out that all such operations can be described as the result of applying interval computations to the corresponding [0,1]-based ones.


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  14. V. Kreinovich, G. C. Mouzouris, and H. T. Nguyen, "Fuzzy rule based modeling as a universal control tool", In: H. T. Nguyen and M. Sugeno (eds.), Fuzzy Systems: Modeling and Control, Kluwer, Boston, Massachusetts, 1998, pp. 135-195.
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