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Master's Dissertation
DOI
10.11606/D.18.2010.tde-20102010-105335
Document
Author
Full name
Eduardo Sacogne Fraccaroli
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2010
Supervisor
Committee
Silva, Ivan Nunes da (President)
Ferasoli Filho, Humberto
Romero, Roseli Aparecida Francelin
Title in Portuguese
Análise de desempenho de algoritmos evolutivos no domínio do futebol de robôs
Keywords in Portuguese
Algoritmos genéticos
RoboCup soccer simulation 2D
Sistemas multiagentes
Abstract in Portuguese
Muitos problemas de otimização em ambientes multiagentes utilizam os algoritmos evolutivos para encontrar as melhores soluções. Uma das abordagens mais utilizadas consiste na aplicação de um algoritmo genético, como alternativa aos métodos tradicionais, para definir as ações dos jogadores em um time de futebol de robôs. Entretanto, conforme relatado na literatura, há inúmeras possibilidades e formas de se aplicar um algoritmo genético no domínio do futebol de robôs. Assim sendo, neste trabalho buscou-se realizar uma análise comparativa dos algoritmos genéticos mono-objetivo e multi-objetivo aplicados no domínio do futebol de robôs. O problema padrão escolhido para realizar essa análise foi de desenvolver uma estratégia de controle autônomo, a fim de capacitar que os robôs tomem decisões sem interferência externa, pois, além de sua solução se encontrar ainda em aberto, o mesmo é também de suma relevância para a área de robótica.
Title in English
Performance analysis of evolutionary algorithms in the robot soccer domain
Keywords in English
Genetic algorithm
Multiagent system
RoboCup soccer simulation 2D
Abstract in English
Many optimization problems in multiagent environments adapt evolutionary algorithms to find the best solutions. A widely used approach consists of applying a genetic algorithm as an alternative to traditional methods, in order to define the actions of the players on a soccer team of simulated robots. However, as reported in the literature, there are many possibilities and ways to apply a genetic algorithm in the field of robot soccer. Therefore, this work attempts to make a comparative analysis of mono-objective and multi-objective genetic algorithms applied to control a robot soccer. The standard problem chosen for this analysis was to develop a strategy for autonomous control, in order to enable the robots to make decisions without external interference, because in addition to its solution is still open, it is also of utmost relevance to the area robotics.
 
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Eduardo.pdf (3.59 Mbytes)
Publishing Date
2010-11-10
 
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