Juan Carlos Galeano

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This paper presents a review of different artificial immune network models, which have been published during the last years. A general model of artificial immune network is presented, which provides a common notation that allows the comparison of different models. A descriptive and comparative analysis is presented emphasizing similarities, differences and(More)
An immune inspired model that can detect anomalies, even when trained only with normal samples, and can learn from encounters with new anomalies is presented. The model combines a negative selection algorithm and a self-organizing map (SOM) in an immune inspired architecture. The proposed system is able to produce a visual representation of the(More)
A model that can detect anomalies, even when trained only with normal samples, and can learn from encounters with new anomalies is proposed. The model combines a negative selection algorithm and a self-organizing map (SOM) in an immune inspired architecture. One of the main advantages of the proposed system is that it is able to produce a visual(More)
— Solution concepts help designing co-evolutionary algorithms by interfacing search mechanisms and problems. This work analyses co-evolutionary dynamics by coupling the notion of solution concept with a Markov chain model of co-evolution. It is shown that once stationarity has been reached by the Markov chain, and given a particular solution concept of(More)
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