This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2012), held in Lugano, Switzerland, in December 2012. The 23 revised full papers presented were carefully reviewed and selected from 40 submissions. They cover topics such as networking, robotics and neural networks, molecular scale and bioinformatics, optimization and bio-inspired modeling in various fields.

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns--phenomena that have fascinated naturalists for centuries--a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world.

Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems?

Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology--a field of study at the forefront of life sciences research.

Social insects such as ants and termites can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. Social insects are also a powerful metaphor for artificial intelligence. The problems they solve - for instance, finding food, dividing labor among nestmates, building nests, and responding to external challenges - have important counterparts in engineering and computer science. This book provides a detailed look at models of social insect behaviour and how these can be applied in the design of complex systems. It draws upon a complementary blend of biology and computer science, including artificial intelligence, robotics, operations research, informationdisplay, and computer graphics. The book should appeal to a broadly interdisciplinary audience of modellers, engineers, neuroscientists, and computer scientists, as well as some biologists and ecologists.

Social insects such as ants and termites can be viewed as powerful problem-solving systems with sophisticated collective intelligence. Composed of simple interacting agents, this intelligence lies in the networks of interactions among individuals and between individuals and the environment. Social insects are also a powerful metaphor for artificial intelligence. The problems they solve - for instance, finding food, dividing labor among nestmates, building nests, and responding to external challenges - have important counterparts in engineering and computer science. This book provides a detailed look at models of social insect behaviour and how these can be applied in the design of complex systems. It draws upon a complementary blend of biology and computer science, including artificial intelligence, robotics, operations research, information display, and computer graphics. The book should appeal to a broadly interdisciplinary audience of modellers, engineers, neuroscientists, and computer scientists, as well as some biologists and ecologists.