The field of Artificial Immune Systems (AIS) concerns the study and development of computationally interesting abstractions of the immune system. This survey tracks the development of AIS since its inception, and then attempts to make an assessment of its usefulness, defined in terms of 'distinctiveness' and 'effectiveness.' In this paper, the standard types of AIS are examined--Negative Select...

1 Polytechnic of Bari, Via E. Orabona 4, 70125 Bari, Italy [email protected] 2 National Cancer Institute ‘Giovanni Paolo II’, Via F. Hahnemann 10, 70126 Bari, Italy [email protected] 3 Federal Technological University of Paraná, Av. 7 de setembro, 3165 Curitba, Brazil [email protected] 4 University of Catania, Viale A. Doria 6, 95125 Catania, Italy [email protected] 5 Computing L...

In this paper, we focus on the potential for applying Kernel Methods into Artificial Immune Systems. This is based on the fact that the commonly employed “affinity functions” can usually be replaced by kernel functions, leading to algorithms operating in the feature space. A discussion of this applicability in negative/positive selection algorithms, the dendritic cell algorithm and immune netwo...

Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration from organisms which possess only innate immune systems, and that AISs should employ syst...

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, de...

Bio-inspired computing has lately demonstrated its usefulness with remarkable contributions to shape detection, optimization, and classification in pattern recognition. Similarly, multithreshold selection has become a critical step for image analysis and computer vision sparking considerable efforts to design an optimal multi-threshold estimator. This paper presents an algorithm for multi-thres...

The immune system is highly distributed, highly adaptive, self-organising in nature, maintains a memory of past encounters and has the ability to continually learn about new encounters. From a computational point of view, the immune system has much to offer by way of inspiration to computer scientists and engineers alike. As computational problems become more complex, increasingly, people are s...

We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of Artificial Immune System (AIS) network models, and we discuss mathematical techniques for analysing the state dynamics o...

Artificial Immune System (AIS) is a new intelligent problem-solving technique that being used in some industrial applications. This paper presents such an immunity-based algorithm for tool breakage detection. The method is inspired by the negative-selection mechanism of the immune system, which is able to discriminate between the self (body elements) and the non-self (foreign pathogens). Howeve...

This review paper attempts to position the area of Artificial Immune Systems (AIS) in a broader context of interdisciplinary research. We review AIS based on an established conceptual framework that encapsulates mathematical and computational modelling of immunology, abstraction and then development of engineered systems. We argue that Artificial Immune Systems are much more than engineered sys...