M. Mukaidono, “Fuzzy deduction of resolution type,” in: R. R. Yager (ed.), Fuzzy Sets and Possibility Theory. Recent Developments [Russian translation], Radio i Sv’yaz, Moscow (1986), pp. 153–161.
D. Dubois and H. Prade, “Necessity and the resolution principle,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 17, No. 3, 474–478 (1987).
C. S. Kim, D. S. Kim, and J. Park, “A new fuzzy resolution principle based on the antonym,” Fuzzy Sets and Systems, Vol. 113, No. 2, 299–307 (2000).
F. A. Fontana and F. Formato, “A similarity-based resolution principle,” International Journal of Intelligent Systems, Vol. 17, No. 9, 853–872 (2002).
S. Raha and K. S. Ray, “Approximate reasoning based on generalised disjunctive syllogism,” Fuzzy Sets and Systems, Vol. 61, No. 2, 143–151 (1994).
H. Habiballa, “Resolution principle in fuzzy predicate logic,” Acta Fac. Paed. Univ. Tyrnaviensis, Ser. C, No. 9 3–12 (2005).
H. Habiballa, “Resolution principle and fuzzy logic,” in: E. Dadios (ed.), Fuzzy Logic — Algorithms, Techniques, and Implementations, Ch. 3, IntechOpen, London (2012), pp. 55–74.
S. D. Shtovba, Design of Fuzzy Systems by Means of MATLAB [in Russian], Hot Line – Telecom, Moscow (2007).
S. Raha, N. R. Pal, and K. S. Ray, “Similarity based approximate reasoning: Methodology and application,” IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Vol. 32, No. 4. 541–547 (2002).
B. Mondal, D. Mazumdar, and S. Raha, “Similarity in approximate reasoning,” International Journal of Computational Cognition, Vol. 4, No. 3, 46–56 (2006).
Mondal B., Raha S. Similarity-based inverse approximate reasoning. IEEE Transaction on Fuzzy Systems, Vol. 19, No. 6. 1058–1071 (2011).
B. Mondal and S. Raha, “Approximate reasoning in fuzzy resolution,” International Journal of Intelligence Science. Vol. 3, No 2, 86–98 (2013).
Yu. Ya. Samokhvalov, “Problem-oriented theorem-proving method in fuzzy logic (PO-method),” Cybernetics and Systems Analysis, Vol. 31, No. 5, 682–690 (1995).
L.A. Zadeh, The Concept of a Linguistic Variable and Its Application to Making Approximate Reasoning [Russian translation], Mir, Moscow (1976).
M. Bofill, G. Moreno, C. Vázquez, and M. Villaret, “Automatic proving of fuzzy formulae with fuzzy logic programming and SMT,” in: Actas de las XIII Jornadas sobre Programacio'n y Lenguajes, PROLE’13, Jornadas SISTEDES, Madrid (2013), pp, 151–165.
Yu. Ya. Samokhvalov, “The Assessment of the administrative decisions validity by fuzzy logic,” USiM, No. 3, 26–34 (2017).
Yu. Ya. Samokhvalov, “Coordination of expert estimates in matrices of preference relations,” USiM, No. 6, 49–53 (2002).
Zwick R., Carlstein E., Budescu D.V. Measures of similarity among fuzzy concepts: A comparative analysis. International Journal of Approximat., Vol. 1, No. 2, 221–242 (1987).
B. Mondal, D. Mazumdar, and S. Raha “Similarity in approximate reasoning,” International Journal of Computational Cognition, Vol. 4, No. 3. 46–56 (2006).
B. M. Wilamowski and J. D. Irwin (eds.), The Industrial Electronics Handbook: Intelligent Systems, CRC Press, Boca Raton (2011).
Yu. Ya. Samokhvalov, “Automatic theorem proving and fuzzy situational search for decisions,” Cybernetics and Systems Analysis, Vol. 37, No. 4, 509–514 (2001).
M. Ford, The Rise of the Robots: Technology and the Threat of Jobless Future, Basic Books, New York (2015).