Šahovski sistem rangiranja za primerjavo evolucijskih algoritmov : doktorska disertacija

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Title:	Šahovski sistem rangiranja za primerjavo evolucijskih algoritmov : doktorska disertacija
Authors:	ID Veček, Niki (Author) ID Mernik, Marjan (Mentor) More about this mentor...
Files:	DR_Vecek_Niki_i2016.pdf (15,24 MB) MD5: CDF5B01B40083F8AC8CF92A812E92A9E
Language:	Slovenian
Work type:	Dissertation
Typology:	2.08 - Doctoral Dissertation
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	Eksperiment na področju evolucijskega računanja lahko povzamemo s štirimi pomembnimi koraki: načrtovanje eksperimenta, zagon eksperimenta, analiza rezultatov ter interpretacija rezultatov in diskusija. Vsak korak zahteva posebno pozornost in vsebuje določene pasti, na katere moramo kot raziskovalci biti pozorni. Disertacija podrobno opiše vse štiri korake, s posebnim poudarkom na statistični analizi rezultatov, in predstavi novo metodo za primerjavo evolucijskih algoritmov - Chess Rating System for Evolutionary Algorithms (CRS4EAs). Predlagana metoda temelji na šahovskem rangiranju, kjer je vsak evolucijski algoritem predstavljen kot šahovski igralec, vsaka primerjava rešitev dveh algoritmov predstavlja igro med dvema igralcema (in se lahko konča z zmago enega in porazom drugega ali remijem), vsaka parna primerjava med več algoritmi pa predstavlja turnir. Osnova za predlagano metodo je šahovski sistem rangiranja Glicko-2, za katerega tekom disertacije tudi pokažemo, da je najprimernejši. Predlagano metodo skozi velik nabor eksperimentov primerjamo s statističnimi testi z ničelno hipotezo in pokažemo, da lahko s predlagano metodo učinkovito primerjamo uspešnosti evolucijskih algoritmov. Predlagana metoda najde podobne signifikantne razlike kot bi jih našli z uporabo standardnih statističnih metod, hkrati pa omogoča absolutno vrednotenje moči in uspešnosti algoritmov, ki so vključeni v sistem. Predlagano metodo na učinkovit način uporabimo za uglaševanje parametrov evolucijskega algoritma in jo skozi nabor več eksperimentov primerjamo z drugimi metodami uglaševanja (F-Race in Revac).
Keywords:	evolutionary algorithms, computational experiment, null hypothesis, glicko, chess rating
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[N. Veček]
Year of publishing:	2016
Year of performance:	2016
Number of pages:	IX, 213 str.
PID:	20.500.12556/DKUM-63656
UDC:	004.832:004.8.021(043.3)
COBISS.SI-ID:	286228224
NUK URN:	URN:SI:UM:DK:KVFZRD6K
Publication date in DKUM:	14.09.2016
Views:	2152
Downloads:	280
Metadata:
Categories:	KTFMB - FERI
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Secondary language

Language:	English
Title:	Chess rating system for evolutionary algorithms
Abstract:	Experiment in the field of evolutionary computing can be summarized with four important stages: experimental design, experiment, analysis, and interpretation of the results and discussion. Each of these stages requires careful attention to avoid the pitfalls. The thesis describes all four stages with special emphasis on the statistical analysis of the results and proposes a new method for comparison and ranking of evolutionary algorithms - Chess Rating System for Evolutionary Algorithms (CRS4EAs). The proposed method is based on chess ranking where each evolutionary algorithm is treated as a chess player, a comparison of the results of two algorithms is treated as one game between these two algorithms (with three possible outcomes: win, loss, or draw), and pairwise comparison of all algorithms is treated as a tournament. The basis of the proposed method is Glicko-2 chess rating system, which showed as the most appropriate one. We have conducted a large number of experiments through the thesis in which the proposed method was compared to different statistical tests of significance. We have shown that the proposed method is appropriate for comparison and ranking of evolutionary algorithms. The proposed method finds similar significant differences as statistical tests, but it also measures the absolute power of algorithms participating in the system. The proposed method can be used as a method for tuning the parameters of an evolutionary algorithm, which was also shown through experiments in which the proposed method was compared to other tuning methods (F-Race and Revac).
Keywords:	evolucijski algoritmi, računski eksperiment, ničelna hipoteza, glicko, šahovski rating

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