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. A teacher's kit
with slides and exercises is available online at
http://baibook.epfl.ch/
http://www.amazon.com/exec/obidos/tg/detail/-/0262062712/
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