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Theoretical advances in artificial immune systems
Authors:J Timmis  A Hone  T Stibor  E Clark
Affiliation:1. Department of Computer Science, University of York, UK;2. Department of Electronics, University of York, UK;3. Institute of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, UK;4. Department of Computer Science, Darmstadt University of Technology, Germany
Abstract:Artificial immune systems (AIS) constitute a relatively new area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different application areas. However, despite these practical successes, until recently there has been a dearth of theory to justify their use. In this paper, the existing theoretical work on AIS is reviewed. After the presentation of a simple example of each of the three main types of AIS algorithm (that is, clonal selection, immune network and negative selection algorithms respectively), details of the theoretical analysis for each of these types are given. Some of the future challenges in this area are also highlighted.
Keywords:Artificial immune systems  Clonal selection  Negative selection  Immune networks  Markov chains  kk-CNF satisfiability" target="_blank">gif" overflow="scroll">k-CNF satisfiability
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