Paper Info
Title
Fuzzy social interaction genetic algorithm
Abstract
This work has the purpose to present a new hybrid metaheuristic developed based on three fundamentals pillars extremely well known: Genetic Algorithms, Game Theory and Fuzzy Systems. This new approach tries to mimic a little bit more closer how a population of individuals evolves along time, like human social evolution emphasizing the social interaction between individuals and the non-binary behavior of human decision making against the classical cooperate-defect behavior present in the Prisoner's Dilemma. In this way it is also presented the SIGA Algorithm [9], the approach of an individual more complex with a genotype composed of two chromosomes, one for the solution of the problem and the other representing its strategy, a binary or fuzzy. Finally some results are presented to an instance of the Traveling Salesman Problem.
Year
DOI
Venue
2010
10.1145/1830761.1830888
GECCO (Companion)
Keywords
Field
DocType
individuals evolves,social interaction genetic algorithm,non-binary behavior,new hybrid metaheuristic,classical cooperate-defect behavior present,fuzzy systems,human social evolution,social interaction,new approach,human decision,game theory,genetic algorithms,traveling salesman problem,fuzzy system,genetic algorithm,it strategy,prisoner s dilemma,social evolution
Population,Mathematical optimization,Social evolution,Computer science,Fuzzy logic,Travelling salesman problem,Artificial intelligence,Game theory,Fuzzy control system,Genetic algorithm,Machine learning,Metaheuristic
Conference
Citations 
PageRank 
References 
0
0.34
3
Authors
6
Name
Order
Citations
PageRank
Otávio Noura Teixeira1117.99
Felipe Houat de Brito252.74
Walter Avelino da Luz Lobato300.68
Artur Noura Teixeira452.40
Carlos Takeshi Kudo Yasojima501.01
Roberto Célio Limão de Oliveira61411.61