Nature-Inspired Computing: Scope and Applications of Artificial Immune Systems Toward Analysis and Diagnosis of Complex Problems

Abstract

The interdisciplinary field of nature-inspired computing is a combination of combining nature computing science of biology, chemistry, physics, engineering, and mathematics which allows the development of new computational hardware, algorithms, or wetware for diagnosing, problem-solving, behaviors of organisms, and synthesis of patterns. Artificial immune systems (AIS) are a sub-field of biologically-inspired computing through machine learning and artificial intelligence (AI). AIS is new algorithm developed from the principles of the human immune system. The AIS is conceptualizing the structure and function of the immune system to computational systems and investigating the applications of the immune system toward solving computational problems. AIS is a dynamic research area used for fault detection, diagnosis, optimization problems, and various approaches to AIS have wide applications. In this chapter, we made an attempt to describe the role of AIS in data analysis and providing solutions for complex diagnostic problems.