Artur Noura Teixeira

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In this paper, it is presented a new way to characterize the phenotype in the context of Genetic Algorithms through the use of Game Theory as a theoretical foundation to define a new phase in the algorithm, named <i>Social Interaction</i>. It is executed before the reproduction phase and allows individuals to fight for their own survival improving their(More)
Genetic Algorithms have been successful in several practical appliances and obtained great prominence among the techniques of Evolutionary Computation. A large portion of methods and parameters adopted in its use are heuristic or random choices, which remain unchanged throughout the execution once they are set. This can lead to a certain lack of exploration(More)
This paper has the purpose to present a new hybrid nature inspired 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(More)
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(More)
This paper presents a new selection method for Genetic Algorithms based upon the concepts of the Evolutionary Game Theory, enabling individuals to compete for available resources. Hence they have the possibility to alter their adaptability and as an effect, assume an influential role on the generation of offspring. The results of some simulations of this(More)
For many years Evolutionary Techniques have been successfully applied in several computational optimization problems. In order for obtain " best results " and a wide exploration of the search surface, the choices for tuning those methods can be exponentially complex and require a large human intervention. Those traditional Darwinian models rely only on(More)
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