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The following are some aspects that need to be addressed in order to make Artificial Immune System as useful problem solving technique:

Artificial immune system (AIS) research in the last five years

IEEE Congress on Evolutionary Computation (1), (2003): 123-130Vol.1

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摘要

Immunity-based techniques are gaining popularity in wide area of applications, and emerging as a new branch of artificial intelligence (AI). The paper surveys the major works in this field during the last five years, in particular, it reviews the works of existing methods and the new initiatives.

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简介
  • Various aspects of biology have always been the inspiration in developing computational models and problem solving methods.
  • The immune system is one such system that has recently drawn significant attention; and as a result, the Artificial Immune System (AIS), has emerged.
  • The immune system, is a system with high complexity and is under active research, likewise the current AIS works adopted only a few immune mechanisms.
  • Three immunological principles are primarily used in a piecemeal in AIS methods.
  • These include the immune network theory, the mechanisms of negative selection, and the clonal selection principles
重点内容
  • Various aspects of biology have always been the inspiration in developing computational models and problem solving methods
  • Three immunological principles are primarily used in a piecemeal in Artificial Immune System methods
  • The following are some aspects that need to be addressed in order to make Artificial Immune System as useful problem solving technique:
结论
  • Artificial Immune Systems (AIS) emerged in the 1990s as a new computational paradigm in AI.
  • They are being used in many applications such as anomaly detection (Dasgupta1999c), pattern recognition (Cao2003), data mining (Knight2002), computer security (Hofmeyr2000, Dasgupta1999d, Kim2002b), adaptive control (Kumar1999, 2003) and fault detection (Bradley2000).
  • Preliminary comparisons have been made between AISs and other soft computing paradigms: ANN, EA, FS, PR.
  • The following are some aspects that need to be addressed in order to make AISs as useful problem solving technique:
表格
  • Table1: A time-line of AIS works (1999-2003)
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基金
  • B cells are connected if the affinities they share exceed a certain threshold, and the strength of the connection is directly proportional to the affinity they share
  • There, T-cells that react against self-proteins are destroyed; only those that do not bind to selfproteins are allowed to leave the thymus
  • The mutation yields a diverse set of antibodies that can be used in the classification procedure
  • To represent the temporal nature of the antigen’s influence, time is added as an additional dimension to the D-W-B-Cell in comparison with the classical B cell node defined in antigen space
  • The main component of NS is the choice of a matching rule, which determines the similarity between two patterns in order to classify self/non-self samples
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