THE XVII CONFERENCE ON FAMEMS AND THE III WORKSHOP ON HILBERT’S SIXTH PROBLEM,KRASNOYARSK,SIBERIA,RUSSIA, 2018 «Rashomon effect»: co∼eventum mechanistic Bayesian great and little theorems and unclarity indexes of co∼events in forensics Oleg Yu. Vorobyev Institute of mathematics and computer science Siberian Federal University Krasnoyarsk mailto:oleg.yu.vorobyev@gmail.com http://olegvorobyev.academia.edu Rustam Bikmurzin Institute of mathematics and computer science Siberian Federal University Krasnoyarsk mailto:bukmurzin.sfe@gmail.com Alexander Bulavchuk Institute of mathematics and computer science Siberian Federal University Krasnoyarsk mailto:bulavchuk@gmail.com Maxim Odnokonnyi Institute of mathematics and computer science Siberian Federal University Krasnoyarsk mailto:maks147833@mail.ru Abstract: The Rashomon effect occurs when an event is given contradictory interpretations by the individuals involved. The effect is named after Akira Kurosawa’s 1950 film Rashomon, in which a murder is described in four contradictory ways by four witnesses [1]. The term addresses the motives, mechanism and occurrences of the reporting on the circumstance and addresses contested interpretations of events, the existence of disagreements regarding the evidence of events and subjectivity versus objectivity in human perception, memory and reporting. Lurking behind the theory of experience and chance, co∼eventum mechanics [2, 3, 4], and our modern understanding of mind and matter is the simple idea of co∼event. And among scientists, there is growing confidence that focusing on a co∼event is becoming more and more productive than it once was. Here we consider the co∼eventum mechanistic approach with the co∼eventum mechanistic Bayesian theorems [5] to analyze the Rashomon case in forensics. Keywords: Eventology, probability theory, event, probability, eventological distribution, Gibbs distribution, Boltzmann distribution, hyperbolic distribution, multivariate distribution, entropy, relative entropy, matter, life, mind, Kolmogorov’s axiomatics, believability, certainty, believability theory, theory of experience and chance, co∼event, co∼eventum mechanics, co∼eventum mechanistic Bayesian theorem, Rashomon effect, forensics. MSC: 60A05, 60A10, 60A86, 62A01, 62A86, 62H10, 62H11, 62H12, 68T01, 68T27, 81P05, 81P10, 91B08, 91B10, 91B12, 91B14, 91B30, 91B42, 91B80, 93B07, 94D05 Contents 1 Witness’s testimony 11 2 Rashomon effect: co∼eventum mechanistic prior matrices and Venn diagrams 12 3 Co∼eventum mechanistic Bayes step-by-step algorithm 14 3.1 Co∼eventum mechanistic Bayes algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4 Co∼eventum mechanistic Bayesian analysis of Rashomon case 15 5 Required theoretical minimum 16 5.1 Co∼event-based Bayesian theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5.2 Co∼event-based Bayesian little theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5.3 Truncated co∼events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 5.4 Unclarity of a co∼event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 6 Computing results 21 c ○ 2018 O.Yu.Vorobyev This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited. Oleg Vorobyev (ed.), Proc. of the XVII FAMEMS’2018, Krasnoyarsk: SFU, ISBN 978-5-9903358-8-2