Open Access
Application areas of AIS: the past, present and future.
Emma Hart,Jon Timmis +1 more
Reads0
Chats0
TLDR
In this paper, the authors take a step back and reflect on the contributions that the Artificial Immune Systems (AIS) has brought to the application areas to which it has been applied, and suggest a set of problem features that they believe will allow the true potential of the immunological system to be exploited in computational systems.Abstract:
After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the
paradigm has brought to the application areas to which it has been applied. Undeniably, there have been a lot of successful stories—however, if the
field is to advance in the future and really carve out its own distinctive niche, then it is necessary to be able to illustrate that there are clear benefits to
be obtained by applying this paradigm rather than others. This paper attempts to take stock of the application areas that have been tackled in the
past, and ask the difficult question ‘‘was it worth it ?’’. We then attempt to suggest a set of problem features that we believe will allow the true
potential of the immunological system to be exploited in computational systems, and define a unique niche for AISread more
Citations
More filters
Proceedings ArticleDOI
Experimental comparisons of Clonal Selection Algorithms with different metadynamics strategies
TL;DR: Four different metadynamics strategies including the traditional metad dynamics strategy and three novel metad Dynamics strategies are tested by experiments to compare their impacts on the performance of CSAs and demonstrate that CSAs without and with different meetadynamic strategies could have different performance.
Proceedings ArticleDOI
A Novel Immune Algorithm for Supervised Classification Problem
TL;DR: A novel immune algorithm based on the risk model, the use of dangerous and hazardous signal mechanism, the risk by assessing the Antigen to the signal classification and use of antibody-Antigen interactions learning mechanisms to make antibodies have strong populations of adaptive learning capacity is presented.
Book ChapterDOI
On the Relevance of Cellular Signaling Pathways for Immune-Inspired Algorithms
Thiago Guzella,T. A. Mota-Santos +1 more
TL;DR: The structure of the NF-κB (NuclearFactor κB) and MAP (Mitogen-activated protein)kinases pathways, and the pathways involved in signaling by Toll-like receptors, are presented and how these pathways could be incorporated in the Dendritic Cell algorithm is considered.
An Artificial Immune Classification and Clustering Systems: A Survey
TL;DR: An effective survey about artificial immune systems which are used in the classification and clustering areas and also make use of the features such as feature selec tion, pattern recognition and machine learning are surveyed.
Dissertation
MAIM: A Novel Island Based Evolutionary Classification Algorithm
Andreas Norstein,Eirik Baug +1 more
TL;DR: A novel hybrid classification algorithm MAIM is proposed, combining AIS with an Island Model Genetic Algorithm (IGA), shown to employ a computationally efficient architecture while simultaneously possessing a generalisation ability on par with several state of the art algorithms.
References
More filters
Journal ArticleDOI
No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Williamson, estimating the support of a high-dimensional distribution
TL;DR: The algorithm is a natural extension of the support vector algorithm to the case of unlabeled data by carrying out sequential optimization over pairs of input patterns and providing a theoretical analysis of the statistical performance of the algorithm.
Journal ArticleDOI
Evolutionary programming made faster
Xin Yao,Yong Liu,Guangming Lin +2 more
TL;DR: A "fast EP" (FEP) is proposed which uses a Cauchy instead of Gaussian mutation as the primary search operator and is proposed and tested empirically, showing that IFEP performs better than or as well as the better of FEP and CEP for most benchmark problems tested.
Journal ArticleDOI
OR-Library: Distributing Test Problems by Electronic Mail
TL;DR: A system (OR-Library) that distributes test problems by electronic mail (e-mail) that has available test problems drawn from a number of different areas of operational research.
Proceedings ArticleDOI
Self-nonself discrimination in a computer
TL;DR: A method for change detection which is based on the generation of T cells in the immune system is described, which reveals computational costs of the system and preliminary experiments illustrate how the method might be applied to the problem of computer viruses.