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A review of the immunological inspired distributed learning environment

The IIDLE is a machine-learning framework inspired by the information processing proper ties of clonal selection in the context of a spatially distr ibuted and recirculation population of lymphocyte in a host organism. The I IDLE may be considered to have been proposed in the context ‘ systems engineer ing’, with a strong top-down and application centric perspective. This work considers the IIDLE in the context of the previously hierarchical framework of the acquired immune system and related models and algor ithms. The main information processing themes of the IIDLE are considered and broader integration of I IDLE and the hierarchal framework is