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Evolution (Biology)

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Natural selection, mutation, and adaptation are well-known and central topics in Darwin's theory of evolution and in the 20th - and 21st -century theories which grew out of it, but many other important topics are used in evolutionary biology that raise interesting philosophical questions. In this book, Elliott Sober analyses a much larger range of topics, including fitness, altruism, common ancestry, chance, taxonomy, phylogenetic inference, operationalism, reductionism, conventionalism, null hypotheses and default reasoning, instrumentalism versus realism, hypothetico-deductivism, essentialism, falsifiability, the principle of parsimony, the principle of the common cause, causality, determinism versus indeterminism, sensitivity to initial conditions, and the knowability of the past. Sober's clear philosophical analyses of these key concepts, arguments, and methods of inference will be valuable for all readers who want to understand evolutionary biology in both its Darwinian and its contemporary forms.

Evolution (Biology) --- Genetics --- Natural selection --- Probabilities --- Philosophy.

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This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains. This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.

Artificial intelligence. --- Machine learning. --- Computational intelligence. --- Evolution (Biology). --- Artificial Intelligence. --- Machine Learning. --- Computational Intelligence. --- Evolutionary Biology.

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The plains vizcacha (Lagostomus maximus) is a remarkable rodent of the Neotropic given several peculiar aspects of its biology, some of them quite unique among rodents or even among mammals. This book gathers specialists studying plains vizcachas from very different approaches, including paleontology, systematics, morphology, physiology, development and conservation. It is divided in two Parts, 1) Evolutionary History, and 2) Morphology, Development and Physiology. It will surely be a required reading for any researcher working with caviomorph rodents, mastozoology of the Neotropics or internal anatomy and physiology of mammals.

Evolution (Biology). --- Paleontology. --- Conservation biology. --- Ecology. --- Vertebrates. --- Anatomy, Comparative. --- Evolutionary Biology. --- Conservation Biology. --- Vertebrate Zoology. --- Animal Anatomy. --- Plains vizcacha.