action-selection mechanism exhibited by the Biological Immune System (BIS). In this section, we initially introduce the immunological metaphors used, followed by a description of the computational counterparts and the explanation of the proposed algorithm.

Immune Metaphors
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The ability of the BIS to learn and quickly counter the effects of a new or already encountered *antigen* provides tremendous insights and motivation to develop powerful yet simple, selection and learning mechanisms to suit distributed computational scenarios. The BIS comprises several types of immune cells such as B-, T-, Killer and Plasma cells, all of which have *antibodies* to recognize and curb the antigens. Immune cells have monospecific antibodies all around it that perform the main task of antigenic recognition. Though different, for simplicity and brevity, we refer to all the immune cells as antibodies. The term antigen has been used synonymously for all types of foreign pathogens. As soon as an antigen is detected within the body of an individual, the process of generating and/or attracting the right kind of antibodies at the site of detection is initiated. The antibodies make their way to the antigenic site through the fluids present inside the body.\
**Cross-Reactivity Threshold ($\epsilon$) :** Each antibody ($Ab$) 