This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (Bionetics). The event took place in the city of York, UK, in December 2011. Bionetics main objective is to bring bio-inspired paradigms into computer engineering and networking, and to enhance the fruitful interactions between these fields and biology. The papers of the conference were accepted in 2 categories: full papers and work-in progress. Full papers describe significant advances in the Bionetics field, while work-in-progress papers present an opportunity to discuss breaking research which is currently being evaluated. The topics are ranging from robotic coordination to attack detection in peer-to-peer networks, biological mechanisms including evolution, flocking and artificial immune systems, and nano-scale communication and networking.

Your immune system is unique. It is in many waysas complex as your brain, but itisnotcentredinonelocation, likethebrain.Itisnotasingleorgan-itconsists ofmanydi?erentcelltypes, diversemethods ofintercellularcommunication, and many di?erent organs. Its functionality is blurred throughout you-we can't extract the immune system, or point to where it begins and ends. The immune system is not separablefrom the system it protects. It has integrallinks to every organ of our bodies. Thishasradicalimplicationsforthe?eldofArti?cialImmuneSystems(AIS), that we are only now beginning to comprehend. One of the ?rst insights is that modelling the immune system, or developing any kind of immune algorithm, is di?cult. The immune system is one aspect of biology that we ?nd di?cult to apply simple reductionist explanations to. We can very successfully extract s- processes of the whole and create immune algorithms based on those processes. But we are always aware that we are missing the whole story. This is leading to more holistic views of immune algorithm development: theoretical analyses of how the sub-components contribute to the whole, and identi?cation of missing elements. Arti?cial immune systems are now beginning to incorporate ideas of innate as well as adaptive immunity, more complex intercellular communication mechanisms, endocrine and neural interfaces, concepts of tissue and broader ideas of organism and environment. SoperhapsthemostexcitingimplicationforthefutureofAISisthatthese- searchersareontheforefrontofunconventionalcomputing-mergingthe bou- aries between biology and traditional computation to achieve new emergent, embodied and distributed processing capabilities.

Artificial Immune Systems (AIS) are adaptive systems inspired by the biological immune system and applied to problem solving. This book provides an accessible introduction that will be suitable for anyone who is beginning to study or work in this area. It gives a clear definition of an AIS, sets out the foundations of the topic (including basic algorithms), and analyses how the immune system relates to other biological systems and processes. No prior knowledge of immunology is needed - all the essential background information is covered in the introductory chapters.Key features of the book include:- A discussion of AIS in the context of Computational Intelligence;- Case studies in Autonomous Navigation, Computer Network Security, Job-Shop Scheduling and Data Analysis =B7 An extensive survey of applications;- A framework to help the reader design and understand AIS;- A web site with additional resources including pseudocodes for immune algorithms, and links to related sites.Written primarily for final year undergraduate and postgraduate students studying Artificial Intelligence, Evolutionary and Biologically Inspired Computing, this book will also be of interest to industrial and academic researchers working in related areas.