Parametric Analysis of Iterated Game Environments as Social Interaction Model for Genetic Algorithm to Solve Constrained Engineering Problems
| Autor: | Marco Antonio Florenzano Mollinetti, Adilson de Almeida Neto, Roberto Célio Limão de Oliveira, Otávio Noura Teixeira, Rodrigo Lisboa Pereira, Mario Tasso Ribeiro Serra Neto, Daniel Leal Souza, Edson Koiti Kudo Yasojima |
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| Rok vydání: | 2018 |
| Předmět: |
Computer Science::Computer Science and Game Theory
Mathematical optimization Process (engineering) ComputingMilieux_PERSONALCOMPUTING 0102 computer and information sciences 02 engineering and technology 01 natural sciences Social relation Alpha (programming language) 010201 computation theory & mathematics Genetic algorithm 0202 electrical engineering electronic engineering information engineering Repeated game 020201 artificial intelligence & image processing Unit-weighted regression Game theory Incidence (geometry) |
| Zdroj: | CEC |
| Popis: | This article presents a parameter study on the applied game theory in Genetic Algorithm (GA), performing an analysis of the game Prisoner's Dilemma applied in the solution of four constrained Engineering problems. Simulations were applied in four different variations of the game, in order to find the best configuration for the analyzed problems. Then, after obtaining the best configuration of the game, we performed an analysis of the incidence of Alpha and Beta weights, present in GA fitness with Social Interaction, using the game that best suited each problem, employing sixteen different weight configurations. At end, the results obtained authenticated the influence of the Social Interaction process in the essence of GA. |
| Databáze: | OpenAIRE |
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