Evolution of Complexity

Simple Simulations of Major Innovations

AvLarry Bull

Häftad, Engelska, 2021

Del 37 i serien Emergence, Complexity and Computation

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Beskrivning

This book gathers together much of the author’s work – both old and new - to explore a number of the key increases in complexity seen in the natural world, seeking to explain each of them purely in terms of the features of fitness landscapes. In a very straightforward manner, the book introduces basic concepts to help readers follow the main ideas. By using variations of the NK model and including the concept of the Baldwin effect, the author presents new abstract models that are able to explain why sources of evolutionary innovation (genomes, symbiosis, sex, chromosomes, multicellularity) have been selected for and hence how complexity has increased over time in some lineages.

Produktinformation

Utgivningsdatum:2021-01-29
Mått:155 x 235 x 6 mm
Vikt:166 g
Format:Häftad
Språk:Engelska
Serie:Emergence, Complexity and Computation
Antal sidor:88
Förlag:Springer Nature Switzerland AG
ISBN:9783030407322

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Mer om författaren

Larry Bull is Professor of artificial intelligence at the University of the West of England (UWE), Bristol, UK. His main research interest is evolution, the computational modelling of natural systems and its use in artificial systems. He has published widely in areas such as artificial life, evolutionary computing, and unconventional computing. Prof Bull was the Founding Editor-in-Chief for the Springer journal Evolutionary Intelligence and has edited a number of books on evolutionary reinforcement learning.

Recensioner i media

“This book offers an excellent entry point for newcomers to research ... . the reader learns about a wide range of fascinating open questions regarding the evolution of complexity. I was truly impressed at the variety of concepts that were touched on. Ultimately, I could absolutely imagine giving this to a new student as a quick introduction to this flavor of research, and I very much enjoyed reading it myself too!” (Emily Dolson, Genetic Programming and Evolvable Machines, Vol. 23 (4), 2022)