A review of the immunological inspired distributed learning environment

The IIDLE is a machine-learning framework inspired by the information processing properties of clonal selection in the context of a spatially distributed and recirculation population of lymphocyte in a host organism. The IIDLE may be considered to have been proposed in the context ‘systems engineering’, 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 algorithms. The main information processing themes of the IIDLE are considered and broader integration of IIDLE and the hierarchal framework is considered.