Biologically inspired systems are currently of great interest to researchers in the software engineering and artificial intelligence (AI) fields. There are two reasons, at least, for such interest. The first is integration. Biological systems are highly integrated dispersed subsystems that work with great collaborative synchronization. The second reason is self-maintenance. In the age of open networks and connected enterprises, self-maintenance is high on the agenda of both software engineers and users. Consequently, this book covers a topic of importance. It focuses particularly on immunity systems, which demonstrate integration and self-maintenance.
The book starts with an introductory chapter, chapter 2, on biological systems. It covers the components of biological systems, introducing hierarchies and additive systems, and self-referencing. The chapter discusses the use of analogy and metaphor in system development, particularly in AI. Chapter 3 continues with the different computationally oriented views of biological systems.
Chapters 4, 5, and 6 discuss, in detail, the immunity-based system models. This starts with a definition of immunity-based systems, in chapter 4, leading to self-organizing network concepts in chapter 5. Chapter 6 discusses sensor networks as self-organizing networks, and the use of immunity-based systems in agents. This chapter paves the way to chapters 7 and 8.
Chapters 7 and 8 cover the multiagent framework and its applications. Chapter 7 discusses the concepts of the framework and an immune algorithm. Chapter 8 looks at an application of this framework to neutralize noise.
Chapter 9 follows on the applications of immune-based systems in a slightly different field of distributed information systems. At this stage, one may hope that security, as an important application of immune systems in developing distributed systems, will be discussed. However, the author takes the agents and robots research viewpoint, and, hence, the focus is still on multiagent systems. Chapter 10 follows on the same track, discussing self-definition and consciousness.
The book, in general, is nicely written, and flows logically from one chapter to another. It covers a very interesting topic, from an agents and robots viewpoint. With the increasing research in cognitive robots and biologically inspired machines, this book is a must-read for new postgraduates and researchers in these fields.
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