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Izpolnljivost logičnih funkcij in evolucija
ID Šircelj, Beno (Author), ID Fijavž, Gašper (Mentor) More about this mentor... This link opens in a new window

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PID: 20.500.12556/rul/353e07b1-1f31-444a-bd60-fb90864c0748

Abstract
V delu smo eksperimentalno ovrednotili rezultate Livnata in soavtorjev (Satisfiability and evolution, FOCS, 2014), ki so pokazali, da populacija naborov slučajne logične funkcije z uporabo šibke selekcije in produktne genetske evolucije konvergira k deležu samih modelov. Preizkuse smo izvajali na družini 28-mestnih logičnih funkcij, v genetskem postopku pa delali s populacijami velikosti 10000. Pri tem smo eksperimentalno potrdili njihove rezultate ter za nekaj dodatnih razredov logičnih funkcij, in ne za zgolj monotone funkcije, pokazali, da genetski postopek k populaciji modelov ravno tako pripelje hitreje kot v splošnem primeru. Eksperimente smo izvedli tudi z uporabo klasičnih reproduktivnih metod genetskih algoritmov, križanja in mutacij. Tudi v tem primeru smo pri slučajno generiranih logičnih funkcijah zaznali konvergenco k populaciji z velikim deležem modelov. Pri nekaterih razredih logičnih funkcij z uporabo križanja in mutacij konvergence k modelom nismo zaznali.

Language:Slovenian
Keywords:genetski algoritem, izpolnljivost izjavnih funkcij, evolucija, šibka selekcija
Work type:Bachelor thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2017
PID:20.500.12556/RUL-95915 This link opens in a new window
Publication date in RUL:25.09.2017
Views:1466
Downloads:319
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Secondary language

Language:English
Title:Satisfiability of logical functions and evolution
Abstract:
This thesis contains experimental evaluation of results of Livnat et al. (Satisfiability and evolution, FOCS, 2014), who have shown that, given a logical function, the population of binary vectors converges to a population of function models, under the assumption of weak selection and product reproduction. Our experiments worked with population size 10000 and genotype length 28. We have experimentally confirmed their theoretical results and for a handful of special logical functions shown that the convergence speed towards the population of models matches the convergence speed of monotone logical functions. We have also run the experiments using crossover and mutations reproduction model. In this case we have for a random logical function experimentally detected convergence towards a population with high ratio of models. However, there are some classes of logical function for which we failed to achieve a similar convergence.

Keywords:genetic algorithm, boolean satisfiability problem, evolution, weak selection

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