Inspired by Darwin’s theory of natural selection to explain the diversity and adaptability of life, Burnet’s clonal selection theory explains the diversity and learning properties of the acquired immune system of vertebrates. In a similar mirroring manner to the field of evolutionary computation that attempts to use the principles of the Darwinian theory and
genetics to address practical engineering problems a new field of study called ‘Clonal Selection Algorithms’ has emerged that attempts the same task by abstracting and applying the principles of Burnet’s foundational immunological theory. This paper provides a summary of this new field of clonal selection algorithms and proposes an algorithm taxonomy a standardized nomenclature and a general model of such algorithms. Finally the field is compared and contrasted to the field of evolutionary computation and general research trends are discussed.