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  • Format: ePub

This book provides an introduction to the significant role of physics in evolution, based on the ideas of matter and energy resource flow, organism self-copying, and ecological change. The text employs these ideas to create quantitative models for important evolutionary processes.

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Produktbeschreibung
This book provides an introduction to the significant role of physics in evolution, based on the ideas of matter and energy resource flow, organism self-copying, and ecological change. The text employs these ideas to create quantitative models for important evolutionary processes.


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Autorenporträt
After getting a PhD in physics at the University of Illinois at Urbana-Champaign, Michael Roth was inspired by Richard Dawkins' The Blind Watchmaker and the study of evolution became a nearly lifelong interest for him. Following a postdoc at Fermilab, he joined The Johns Hopkins University Applied Physics Laboratory (JHUAPL) where he served in many scientific leadership roles until retirement. He has major publications in several fields including theoretical physics, geophysics, neural networks (aka deep learning), biophysics, and instrumentation. He was a Co-Chairman for several conferences. He has also served as a JHUAPL group supervisor and as the Book Review Editor and Editor-in-Chief of IEEE Transactions on Neural Networks. After retirement from JHUAPL, he devoted his time to his longtime interest in evolution.

Rezensionen
'There are not many works in the literature that take the point of view taken by "The Physics of Evolution", [...] Michael Roth points at an important and, in our community, often overlooked aspect of evolution: How the change in the environment can impact the course of evolution, and thereby become a driving force for complexity in the world around us. I wished more people in our community which studies artificial evolutionary systems would start applying lessons from ecology to make more progress on the question of open-endedness in the evolution of their systems.'

Wolfgang Banzhaf, Founding Editor of Genetic Programming and Evolvable Machines