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...

The Artificial Immune Intelligent Maintenance System (AI2MS) is an architecture proposal for a Distributed Intelligent Maintenance System (IMS) using Artificial Immune Systems concepts. Equipment has its own embedded AIS, performing a local diagnosis. This proposal is modeled and implemented using multiagent systems, where every autonomous IMS is mapped to a set of local agents, while the commu...

University timetabling problem is a very common and seemingly simple, but yet very difficult problem to solve in practice. While solution definitely exists (evidenced by the fact that we do hold classes), an automated optimal schedule is very difficult to derive at present. There were successful attempts to address this problem using heuristics search methods. However, until now, university tim...

Associative classification algorithms which are based on association rules have performed well compared with other classification approaches. However a fundamental limitation with these classification algorithms is that the search space of candidate rules is very large and the processes of rule discovery and rule selection are conducted separately. This paper proposes an approach called ARMBIS,...

Recent years have seen a dramatic increase in the application of biologically-inspired algorithms to business problems. Applications of neural networks and evolutionary algorithms have become common. However, as yet there have been few applications of artificial immune systems (AIS), algorithms that are inspired by the workings of the natural immune system. The natural immune system can be cons...

Artificial Immune Systems (AIS) combine a priori knowledge with the adapting capabilities of biological immune systems to provide a powerful alternative to currently available techniques for pattern recognition, modeling, design, and control. Immunology is the science of built-in defense mechanisms that are present in all living beings to protect against external attacks. A biological immune sy...

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...

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...

3 Artificial Immune Networks as a coevolutionary model 5 4 A new Immune Network model 6 4. 6 Theoretical analysis of the model 8 6.

This paper presents an agent-based artificial immune system approach for adaptive damage detection in distributed monitoring networks. The presented approach establishes a new monitoring paradigm by embodying desirable immune attributes, such as adaptation, immune pattern recognition, and selforganization, into monitoring networks. In the artificial immune system-based paradigm, a group of auto...