"Bio-Inspired Artificial Intelligence brings together all the things I've been interested in for the last 25 years, and surprises me by providing a coherent intellectual framework for them all. This book is a treasure trove of history from Darwin to Gibson and Walter, an unambiguous tutorial on how to build a plethora of computational models, and a healthy exploration of the philosophies that have driven wide ranging research agendas."
—Rodney Brooks, Panasonic Professor of Robotics, Department of Electrical Engineering and Computer Science, MIT
"Competent, lucid, well-written, Bio-Inspired Artificial Intelligence contains precisely the material you want from a comprehensive textbook, with many highly informative examples from biology, engineering, and computing. This book has the potential to become the new standard in the artificial intelligence field."
—Rolf Pfeifer, Director, Artificial Intelligence Laboratory, University of Zurich
"Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, by
Dario Floreano and Claudio Mattiussi, ...discusses biological and artificial
systems that operate at a wide range of time and space scales, but manages to move
fluently from slow evolutionary time, to life-time learning, to real time adaptation.
I found this book notable for at least two
reasons. First, it provides a coherent intellectual framework to organize all these
computational developments by grounding them in their biological nature and in the
pervasiveness of evolution throughout biology. Second, it provides a clear, well written,
comprehensive, and authoritative account of these developments in an
educational format well suited for a classroom.
In the preface, the authors state their hope for their book to be instructive and
useful for a wide audience. Their hope is well founded. I think this book is well
suited for various audiences. First, the text is ideal for a graduate level course; ... This book is also a very
complete reference and catalog of biologically inspired methods well suited for
researchers, graduate students and engineers in the field of computer science.
Finally, save for few technical sections, the vast majority of the book is very
accessible, engaging to read and easy to follow. It is definitely a good introduction
for anybody interested in biologically inspired artificial intelligence.
In summary, Floreano and Mattiussi deliver a great book that I highly
— Ivan Garibay, University of Central Florida, Orlando
The complete review can be found in the September 2010 issue of the journal Genetic Programming and Evolvable Machines.
"This is a book that bridges biological systems and computer science. For digital-based researchers, having this book which details the biological components of natural life and seamlessly integrates that knowledge into our digital realm is an essential asset. Each chapter is systematically introduces the reader to a biological system while easing them into its computational counterpart. ... This theme of progression from biological introduction to digital computation is reproduced as a single voice through out each chapter. The fundamentals of Bio-Inspired Artificial Intelligence are well demonstrated, allowing for a novice researcher in this area to develop the necessary skills and have a firm grasp on this topic.
For myself, the quality of this book can simply be noted by the publishers, MIT Press. Many of the best books I have encountered in my studies have been published by MIT, and here is another. Floreano and Mattiussi have not let me down in their quality...
Overall, if you are interested in this field, buy this book. ... This book will make an excellent addition to any computer researchers library."
—Anthony Kulis, Department of Computer Science, Southern Illinois University
The complete review can be found in the December 2009 issue of Scalable Computing: Practice and Experience (Volume 10, Number 4, pp. 443–444)
"This book brings together
both fields to review a selection of the component fields of
AI in the light of biology.
The book is primarily aimed at undergraduate computer
scientists but should also be useful for biologists
interested in gaining an overview of the field. As with all
inter-disciplinary texts, it has to steer a difficult path
between providing enough detail and depth, while avoiding
overwhelming readers with technical detail. It generally
succeeds, though as a biologist interested in AI, my
viewpoint is mainly from one side of the disciplinary fence.
Indeed, books like this are important in removing the disciplinary
fence entirely, so that we can each learn from
advances in the other field.
The relative proportions of biology and
AI in each chapter vary substantially, but biologist readers
may find that the way in which engineers frame biological
problems illuminating, even if it is unfamiliar.
[T]his book is
an ambitious, and mostly successful, attempt to bring together
two different fields. It is a useful and very timely
addition to the library of both AI undergraduates wishing
to broaden their horizons, and of biologists (at any level)
interested in AI and needing an overview of the area."
—Jackie Chappell, University of
The complete review can be found in the September/October 2009 issue of the American Journal of Human Biology
"In this comprehensive, well-written book, respected experts Floreano and Mattiussi (Swiss Federal Institute of Technology, Lausanne) provide a systematic introduction to the theories and methods of bio-inspired artificial intelligence. The material is organized in seven chapters: "Evolutionary Systems," "Cellular Systems," "Neural Systems," "Developmental Systems," "Immune Systems," "Behavioral Systems," and "Collective Systems."
The book introduces these systems by presenting the underlying biological theories, followed by descriptions of related engineering methods and technologies. The chapters guide the reader through biological and artificial systems that operate at different temporal and spatial scales: on the temporal scale, progressing from systems that change at a slow evolutionary pace to those that interact in real time, and on the spatial scale, from cells and neurons to societies of individuals, Illustrative sample software and hardware technologies accompany the theories and methods presented.
Summing Up: Highly recommended, Graduate students, researchers, faculty, and professionals."
—C. Tappert, Pace University
This review appeared in the April 2009 issue of CHOICE