Immunology as a Metaphor for Computational ... - Napier University

Chapter 2. Background 41environments.The preceding sections have presented an overview of the main techniques used toimplement artificial immune systems. Furthermore, a detailed summary of the literaturerelating to the topics of interest in this thesis has been given. The field is expandingrapidly however, and there are many more examples of AIS in the literature than couldbe described in this thesis. The interested reader is referred to a detailed bibliographycontaining 293 references produced by [Dasgupta et al., 2002] — this bibliographycontains a wide variety of applications, implemented using variations on one or moreof the techniques described in this chapter.2.7 Sparse Distributed Memories and their Relationshipto Immunological MemorySmith et. al have shown that immunological memory is a member of a class of sparseand distributed associative memories. Another type of memory typical of this class isKanerva’s Sparse Distributed Memory, or SDM [Kanerva, 1988]. The work presentedin chapters 5 and 6 of this thesis draws heavily on the analogy between the SDM andthe immune system, and hence a brief description of the SDM is now presented tooutline the underlying concepts so that the correspondence between the two types ofmemory can be made clear. A more detailed discussion of the properties of the SDMis provided later in this thesis in chapters 4 and 6.2.7.1 Kanerva’s modelThe SDM is a form of memory which can be written to by providing an address anddata, and then read from by providing an address and getting an output. The SDM isspecifically designed to function with enormous address spaces, in which it would beimpossible to physically instantiate all of the possible address locations. For example,SDM can cope with addresses of 1000 bits, and therefore 2 1000 potential addressdatalocations. An SDM instantiates a small and random subset of these locations,which are referred to as hard locations, and are said to sparsely cover the input space