ISSN 2071-8594

Russian academy of sciences


Gennady Osipov

V.K. Finn Heuristics of empirical regularities discovering and principles of knowledge discovery


Federal Research Centre “Informatic and Control” Russian Academy of Sciences, Moscow, Russia The paper formulates the logical means of implementing the heuristics of empirical regularities discovering by means of JSM reasoning and JSM research. The considered heuristics is based on the synthesis of induction, analogy and two kinds of abduction. It also makes use of possible extensions of sequences of fact bases and causal forcing and corresponding modalities determined through them.


JSM Method, JSM reasoning, JSM research, induction, analogy, abduction of the 1st an 2nd kind, causal forcing, JSM heuristics, empirical regularities.

PP. 3-19.

DOI 10.14357/20718594180311


1. Anshakov, O.M., ed. 2009. DSM metod avtomaticheskogo porozhdeniya gipotez: logicheskie I epistemologicheskie osnovaniya [JSM Method of Automatic Hypotheses Generation: Logical and Epistemological Foundation]. Moscow: LIBROCOM. 432 p.
2. Finn, V. K. 2014. Epistemological Foundations of the JSM Method for Automatic Hypothesis Generation. Automatic Documentation and Mathematical Linguistics. 48 (2): 96–148.
3. Finn, V. K. 2017. On the Class of JSM Reasoning That Uses the Isomorphism of Inductive Inference Rules. Scientific and Technical Information Processing. 44 (6): 387–396.
4. Finn, V. K. 2011. Iskusstvenny intellect: metodologiya, primeneniya, filosofiya [Artificial intelligence: methodology, applications, philosophy]. Moscow: KRASAND. 448 p.
5. Finn, V. K., and Shesternikova, O.P. 2017. On JSM Reasoning Applicable to Unions of Factbase Subsets. Automatic Documentation and Mathematical Linguistics. 51 (5): 220–234 (Part 1); 51 (6): 266–288 (Part 2).
6. Finn, V. K. 2014. Distributive Lattices of Inductive JSM Procedures. Automatic Documentation and Mathematical Linguistics. 48 (6): 265–295.
7. Finn, V. K. 2009. Avtomaticheskoe porozhdenie gipotez v intellectual’nykh sistemakh [Automatic Hypotheses Generation in Intelligent Systems]. Moscow: LIBROCOM. 528 p.
8. Shesternikova, O.P., Agafonov, M.A., Vinokurova, L.V., Pankratova, E.S., and Finn, V.K. 2016. Intelligent System for Diabetes Prediction in Patients with Chronic Pancreatitis. Scientific and Technical Information Processing. 43 (5-6): 315–345.
9. Shesternikova, O.P. 2016. O primenenii intellectual’noy sistemy prognozirovaniya razviniya diabetom u bol’nykh pankreatitom [On the Use of Intelligent System for Diabetes Prediction in Patients with Chronic Pancreatitis]. Iskusstvenny intellect i prinyatie resheniy [Artificial Intelligence and Decision Making] 3: 62–71.
10. Agafonov, M.A., Shesternikova, O.P., Vinokurova, L.V., Pankratova, E.S., and Finn, V.K. 2017. O printsipakh i logicheskikh sredstvakh, realizuemykh v intellectual’noy sisteme dlya gastroenterologii [On Principles and logical tools implemented in Intelligent System for gastroenterology]. Nauchno-technicheskaya informatsiya. Seria 2 [Scientific and Technical Information. Series 2] 3: 16–39.
11. Klimova, S.G., Mikheyenkova, M.A., and Finn, V.K. 2016. DSM Metod v kachestvennom sociologicheskom issledovanii: osnovnye printsipy i opyt ispol’zovaniya [JSM Method in Qualitative Sociological Research: the Main Principles and the Use Experience]. Sociologichesky zhurnal [Sociological Magazine] 22 (2): 8–30
12. Vinokurova, L.V., Agafonov, M.A., Varvanina, G.G., Finn, V.K., Pankratova, E.S., and Dobrynin D.A. 2014. Primenenie intellectual’noy sistemy tipa DSM dlya analiza klinicheskikh dannykh [The Use of Intelligent System of JSM Type for Clinical Data Analysis]. Rossiysky bioterapevtichesky zhurnal [Russian Magazine of Biotherapy] 13 (3): 57–60.
13. Polya, G. 1957. How to Solve It. Garden City, NY: Doubleday. 253 p.
14. Neizvestny D.A. Pospelov: stanovlenie II v SSSR i Rossii [Disclosed D.A. Pospelov: the Development of AI in the USSR and Russia]. 2017. Moscow: URSS.
15. Polya, G. 1954. Mathematics and Plausible Reasoning. Princeton University Press. 296 р.
16. Finn, V.K., Shesternikova O.P. 2018. Evristica obnaruzheniya empiricheskikh zakonomernostey posredstvom DSM rassuzhdeniy [The Heuristics of Empirical Regularities discovering by JSM Reasoning]. Nauchno-technicheskaya informatsiya. Seria 2 [Scientific and Technical Information. Series 2] №9, pp 7-42.
17. Ed. Barwise, J. 1977. Handbook of Mathematical Logic. Amsterdam, New York, Oxford: North-Holland Publishing Company. 1166 p.
18. Skvortsov, D.P. 1983. O nekotorykh sposobakh postroeniya logicheskikh yazykov s kvantorami po kortezham [On some ways of constructing languages with quantifier on the tuples]. Semiotica i informatica [Semiotics and Informatics] 20: 102–126.
19. Rosser, J.B., and Turquette, A.R. 1958. Many-Valued Logics. Amsterdam: North-Holland Publishing Company. 124 р.
20. Finn, V.K. 2011. J.S. Mill’s Inductive Methods in Artificial Intelligence Systems. Scientific and Technical Information Processing. 38 (6): 315–345 (Part 1); 39 (5): 241–260 (Part 2).
21. Mill, J.S. 1843. A System of Logic Ratiocinative and Inductive, being a connected View of the Principles of Evidence and the Methods of Scientific Investigation. London: Parker, Son and Bowin. 569 р.
22. Rescher, N. 1973. The coherence theory of truth. Oxford: The Clarendon Press. 388 р.
23. Anshakov, O.M., Finn, V.K., and Skvortsov, D.P. 1989. On Axiomatization of Many-Valued Logics Associated with Formalization of Plausible Reasoning. Studia Logica. XLVIII (4): 423–447.
24. Finn, V. K. 2015. Detecting Empirical Regularities in Bases of Facts Using JSM Reasoning. Automatic Documentation and Mathematical Linguistics. 49 (4): 122–151.
25. Peirce, C.S. 1934. Collected papers of Charles Sanders Peirce. Vol. 5. Cambridge, MA: Harvard University Press. 189 р.
26. Kapitan T. 1992. Peirce and the Autonomy of Abductive Reasoning. Erkenntnis. 37 (1): 1–26.
27. Chellas, B.F. 1980. Modal Logic: An Introduction. Cambridge University Press. 299 p.
28. Popper, K.P. 1979. Objective Knowledge: An Evolutionary Approach. Oxford: At the Clarendon Press. 407 p.