Application of Genetic Programming and Genetic Algorithm in Evolving Emotion Recognition Module

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@InProceedings{Yusuf:2015:CEC,

• author = "Rahadian Yusuf and Ivan Tanev and Katsunori Shimohara",
• title = "Application of Genetic Programming and Genetic Algorithm in Evolving Emotion Recognition Module",
• booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015)",
• year = "2015",
• editor = "Yadahiko Murata",
• pages = "1444--1449",
• address = "Sendai, Japan",
• month = "25-28 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CEC.2015.7257058",
• abstract = "This paper will discuss about implementation of a voting system and weighted credibility to augment evolution process of an emotion recognition module. The evolution process of the emotion recognition module is one part of ongoing research on designing an intelligent agent capable of emotion recognition, interaction, and expression. Genetic programming evolves the classifiers, while genetic algorithm evolves the weighted credibility as a modification of parallel voting systems. The experimental results suggest that the implementation of weighted credibility evolution improves the performance of training, in the form of significantly reduced training time needed.",
• notes = "1710 hrs 15440 CEC2015",

}

Genetic Programming entries for Rahadian Yusuf Ivan T Tanev Katsunori Shimohara

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