We present a simplified view of those parts of the human immune system which can be used to provide the basis for a data analysis tool. The motivation for and reasoning behind such a model is given and the desire for a 'transparent' model and meaningful visualization and interpretation techniques is noted. A minimalist formulation of an artificial immune system and some of its behaviour is desc...

We propose an efficient method of extracting knowledge when scheduling parallel programs onto processors using an artificial immune system (AIS). We consider programs defined by Directed Acyclic Graphs (DAGs). Our approach reorders the nodes of the program according to the optimal execution order on one processor. The system works in either learning or production mode. In the learning mode we u...

As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some have argued that this concept in the context of AIS brings little novelty to the already saturated field of the immune inspired computational research. This article aims to show that such a component of an AIS has the po...

Through time, many software engineering fundamentals change such as programming languages, paradigms and development teams. These changes affect test suites; if these suites do not evolve, they will wear out. Mutation testing is a computationally expensive, fault-based testing method. By using high quality test data however, only a minimal number of mutations are required, allowing changes in t...

absTracT Many immue-inspired algorithms are based on the abstractions of one or several immunology theories, such as clonal selection, negative selection, positive selection, rather than the whole process of immune response to solve computational problems. In order to build a general computational framework by simulating immune response process, this chapter introduces a population-based artifi...

This paper proposes an affinity based complex artificial immune system considering the fact that the different eptitopes located on the surface of antigen can be recognized by a set of different paratopes expressed on the surface of immune cells. A neighborhood set consisting of immune cells with different affinities to a certain input antigen is built to simulate the nature immune behavior. Fu...

The Biological Immune System is a remarkable information processing and self-learning system that offers stimulation to build Artificial Immune System (AIS).During the last two decades, the field of AIS is progressing slowly and steadily as a branch of Computational Intelligence (CI). At present the AIS algorithms such as Negative Selection Theory, Clonal Selection Theory, Immune Networks Theor...

The university timetabling, examination and course, are known to be highly constrained optimization problems. Metaheuristic approaches, and their hybrids, have successfully been applied to solve the problems. This paper presents three artificial immune algorithms, the algorithms inspired by the immune system, for university timetabling; clonal selection, immune network and negative selection. T...

We describe an artificial immune system (AIS) that is distributed, robust, dynamic, diverse and adaptive. It captures many features of the vertebrate immune system and places them in the context of the problem of protecting a network of computers from illegal intrusions.

In this thesis, the uses of Artificial Immune Systems (AIS) in Machine learning is studded. the thesis focus on some of immune inspired algorithms such as clonal selection algorithm and artificial immune network. The effect of changing the algorithm parameter on its performance is studded. Then a new immune inspired algorithm for unsupervised classification is proposed. The new algorithm is bas...