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Biological systems have become highly significant for traditional computer architectures as examples of highly complex self-organizing systems that perform tasks in parallel with no centralized control. However, few researchers have compared the suitability of different computing approaches for the unique features of Artificial Immune Systems (AIS) when trying to introduce novel computing architectures, and few consider the practicality of their solutions for real world machine learningdoi:10.1109/ssci.2016.7850157 dblp:conf/ssci/DengBM16 fatcat:34jvqp74ojcijdz4np6c7ekzsi