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An overview of current models of biological systems, reflecting the major advances that have been made over the past decade.
In this candid and witty autobiography, Nobel laureate Herbert A. Simon looks at his distinguished and varied career, continually asking himself whether (and how) what he learned as a scientist helps to explain other aspects of his life. A brilliant polymath in an age of increasing specialization, Simon is one of those rare scholars whose work defines fields of inquiry. Crossing disciplinary lines in half a dozen fields, Simon's story encompasses an explosion in the information sciences, the transformation of psychology by the information-processing paradigm, and the use of computer simulation for modeling the behavior of highly complex systems. Simon's theory of bounded rationality led to a Nobel Prize in economics, and his work on building machines that think—based on the notion that human intelligence is the rule-governed manipulation of symbols—laid conceptual foundations for the new cognitive science. Subsequently, contrasting metaphors of the maze (Simon's view) and of the mind (neural nets) have dominated the artificial intelligence debate. There is also a warm account of his successful marriage and of an unconsummated love affair, letters to his children, columns, a short story, and political and personal intrigue in academe.
The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. In a unified, systematic presentation, this monograph fully details those models and explores areas of accelerated life testing usually only touched upon in the literature. Accelerated Life Models:
Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains - "Artificial Life Models in Hardware" offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems. Ideas and implementations of living phenomena in non-living substrates cast a colourful picture of state-of-art advances in hardware models of artificial life.
The advent of powerful processing technologies and the advances in software development tools have drastically changed the approach and implementation of computational research in fundamental properties of living systems through simulating and synthesizing biological entities and processes in artificial media. Nowadays realistic physical and physiological simulation of natural and would-be creatures, worlds and societies becomes a low-cost task for ordinary home computers. The progress in technology has dramatically reshaped the structure of the software, the execution of a code, and visualization fundamentals. This has led to the emergence of novel breeds of artificial life software models, including three-dimensional programmable simulation environment, distributed discrete events platforms and multi-agent systems. This second edition reflects the technological and research advancements, and presents the best examples of artificial life software models developed in the World and available for users.
An informal introduction and guidance to modern software tools for modeling and simulation of life-like phenomena, this book offers detailed reviews of contemporary software for artificial life for both professionals and amateurs.
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Features an authentic and engaging approach to mathematical modeling driven by real-world applications With a focus on mathematical models based on real and current data, Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® guides readers in the solution of relevant, practical problems by introducing both mathematical and Excel techniques. The book begins with a step-by-step introduction to discrete dynamical systems, which are mathematical models that describe how a quantity changes from one point in time to the next. Readers are taken through the process, language, and notation required for the construction of such models as well as their implementation in Excel. The book examines single-compartment models in contexts such as population growth, personal finance, and body weight and provides an introduction to more advanced, multi-compartment models via applications in many areas, including military combat, infectious disease epidemics, and ranking methods. Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® also features: A modular organization that, after the first chapter, allows readers to explore chapters in any order Numerous practical examples and exercises that enable readers to personalize the presented models by using their own data Carefully selected real-world applications that motivate the mathematical material such as predicting blood alcohol concentration, ranking sports teams, and tracking credit card debt References throughout the book to disciplinary research on which the presented models and model parameters are based in order to provide authenticity and resources for further study Relevant Excel concepts with step-by-step guidance, including screenshots to help readers better understand the presented material Both mathematical and graphical techniques for understanding concepts such as equilibrium values, fixed points, disease endemicity, maximum sustainable yield, and a drug’s therapeutic window A companion website that includes the referenced Excel spreadsheets, select solutions to homework problems, and an instructor’s manual with solutions to all homework problems, project ideas, and a test bank The book is ideal for undergraduate non-mathematics majors enrolled in mathematics or quantitative reasoning courses such as introductory mathematical modeling, applications of mathematics, survey of mathematics, discrete mathematical modeling, and mathematics for liberal arts. The book is also an appropriate supplement and project source for honors and/or independent study courses in mathematical modeling and mathematical biology. Jeffrey T. Barton, PhD, is Professor of Mathematics in the Mathematics Department at Birmingham-Southern College. A member of the American Mathematical Society and Mathematical Association of America, his mathematical interests include approximation theory, analytic number theory, mathematical biology, mathematical modeling, and the history of mathematics.
Conflicting Models for the Origin of Life Conflicting Models for the Origin of Life provides a forum to compare and contrast the many hypotheses that have been put forward to explain the origin of life. There is a revolution brewing in the field of Origin of Life: in the process of trying to figure out how Life started, many researchers believe there is an impending second creation of life, not necessarily biological. Up-to-date understanding is needed to prepare us for the technological, and societal changes it would bring. Schrodinger’s 1944 “What is life?” included the insight of an information carrier, which inspired the discovery of the structure of DNA. In “Conflicting Models of the Origin of Life” a selection of the world’s experts are brought together to cover different aspects of the research: from progress towards synthetic life – artificial cells and sub-cellular components, to new definitions of life and the unexpected places life could (have) emerge(d). Chapters also cover fundamental questions of how memory could emerge from memoryless processes, and how we can tell if a molecule may have emerged from life. Similarly, cutting-edge research discusses plausible reactions for the emergence of life both on Earth and on exoplanets. Additional perspectives from geologists, philosophers and even roboticists thinking about the origin of life round out this volume. The text is a state-of-the-art snapshot of the latest developments on the emergence of life, to be used both in graduate classes and by citizen scientists. Audience Researchers in any area of astrobiology, as well as others interested in the origins of life, will find a modern and current review of the field and the current debates and obstacles. This book will clearly illustrate the current state-of-the-art and engage the imagination and creativity of experts across many disciplines.
This open access book explores the field of life science business from a multidisciplinary perspective. Applying statistical, mathematical, game-theoretic, and data science tools to pharmaceutical and biotechnology business endeavors, the book describes value creation, value maintenance, and value realization in the life sciences as a sequence of processes using the quantitative language of applied mathematics. Written by experts from a variety of fields, the contributions illustrate the shift from a deterministic to a stochastic view of the processes involved, offering a new perspective on life sciences economics. The book covers topics such as valuing and managing intellectual property in life science, licensing in the pharmaceutical business, outsourcing pharmaceutical R&D, and stochastic modelling of a pharmaceutical supply chain. The book will appeal to scholars of economics and the life sciences, as well as to professionals in chemical and pharmaceutical industries.