@inproceedings{38149070886,
    abstract = "We propose in this paper an artificial immune system to solve CSPs. The algorithm has been designed following the framework proposed by de Castro and Timmis. We have calibrated our algorithm using Relevance Estimation and Value Calibration (REVAC), that is a new technique, recently introduced to find the parameter values for evolutionary algorithms. The tests were carried out using random generated binary constraint satisfaction problems on the transition phase where are the hardest problems. The algorithm shown to be able to find quickly good quality solutions. © Springer-Verlag Berlin Heidelberg 2007.",
    year = "2007",
    title = "NAIS: A calibrated immune inspired algorithm to solve binary constraint satisfaction problems",
    volume = "4628 LNCS",
    pages = "25-34",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    author = "Zúñiga, Marcos D. and Montero, Elizabeth and Riff Rojas, Maria Cristina"
}

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