A comprehensive introduction to new approaches in artificial
intelligence and robotics that are inspired by self-organizing
biological processes and structures.
New approaches to artificial intelligence spring from the idea that
intelligence emerges as much from cells, bodies, and societies as it
does from evolution, development, and learning. Traditionally,
artificial intelligence has been concerned with reproducing the
abilities of human brains; newer approaches take inspiration from a
wider range of biological structures that that are capable of autonomous
self-organization. Examples of these new approaches include evolutionary
computation and evolutionary electronics, artificial neural networks,
immune systems, biorobotics, and swarm intelligence--to mention only a
few. This book offers a comprehensive introduction to the emerging field
of biologically inspired artificial intelligence that can be used as an
upper-level text or as a reference for researchers. Each chapter
presents computational approaches inspired by a different biological
system; each begins with background information about the biological
system and then proceeds to develop computational models that make use
of biological concepts. The chapters cover evolutionary computation and
electronics; cellular systems; neural systems, including neuromorphic
engineering; developmental systems; immune systems; behavioral
systems--including several approaches to robotics, including
behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and
collective systems, including swarm robotics as well as cooperative and
competitive co-evolving systems. Chapters end with a concluding overview
and suggested reading.
