A combination of old, sometimes revisited, and new natural computing algorithms, this book is arranged almost chronologically. Part 1, for example, is about the now old discipline of evolutionary computation and genetic algorithms, where one can find the usual references to various mostly well-known textbook topics. Part 2 is based on social computing, such as swarm computing for optimization, followed by a part on neuro-based computation such as neural networks in all their flavors as usually classified into supervised and unsupervised approaches. Part 4, one of the most interesting from my point of view, is on computation based or inspired by the natural immune system. The basics of immunology are very well explained, at least those that serve as a basis for some immune system-inspired algorithms. Part 5 touches on more recent and trendy topics such as grammatical computing and the so-called L-systems, including a chapter devoted to a more exclusively biological topic: genetic regulatory networks. Part 6 is devoted to computation based on more physical roots, such as quantum computing. This particular part feels like it is not thoroughly covered; it could have ranged over at least two parts and gone beyond quantum computing into more dynamic systems, or even more fundamentally, billiard computing, Landauer’s principles, and reversible computing with connections to thermodynamics. Part 7 discusses other paradigms, including plant-inspired and chemically inspired algorithms. Part 8 falls short, as it is devoted to the future of naturally inspired algorithms, but covers only a handful of possible ideas.

The introduction discusses the current landscape of nature-inspired algorithms according to the authors, but seems to miss some areas of exploration such as slime mold computing that generated some interest about a decade ago. It also misses some more sophisticated theory, such as the application of complexity and machine learning to biological problems represented as graphs and networks (for example, network biology). One interesting advantage of the volume is that it was prepared by and for scholars that are not necessarily in computer science. The book is definitely a good reference and a well-written and well-explained introduction to natural computing, even if at times it feels a bit dated and incomplete.