Life Models

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.

An overview of current models of biological systems, reflecting the major advances that have been made over the past decade.

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:

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.

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.

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.

Drawing on a combination of perspectives from diverse fields, this volume offers an anthropological study of climate change and the ways in which people attempt to predict its local implications, showing how the processes of knowledge making among lay people and experts are not only comparable but also deeply entangled. Through analysis of predictive practices in a diversity of regions affected by climate change – including coastal India, the Cook Islands, Tibet, and the High Arctic, and various domains of scientific expertise and policy making such as ice core drilling, flood risk modelling, and coastal adaptation – the book shows how all attempts at modelling nature’s course are deeply social, and how current research in "climate" contributes to a rethinking of nature as a multiplicity of modalities that impact social life.

Broadly speaking, there are two general approaches to teaching mathematical modeling: 1) the case study approach, and 2) the method based approach (that teaches mathematical techniques with applications to relevant mathematical models). This text emphasizes instead the scientific issues for modeling different phenomena. For the natural or harvested growth of a fish population, we may be interested in the evolution of the population, whether it reaches a steady state (equilibrium or cycle), stable or unstable with respect to a small perturbation from equilibrium, or whether a small change in the environment would cause a catastrophic change, etc. Each scientific issue requires an appropriate model and a different set of mathematical tools to extract information from the model. Models examined are chosen to help explain or justify empirical observations such as cocktail drug treatments are more effective and regenerations after injuries or illness are fast-tracked (compared to original developments). Volume I of this three-volume set limits its scope to phenomena and scientific issues that are modeled by ordinary differential equations (ODE). Scientific issues such as signal and wave propagation, diffusion, and shock formation involving spatial dynamics to be modeled by partial differential equations (PDE) will be treated in Vol. II. Scientific issues involving randomness and uncertainty are examined in Vol. III. Request Inspection Copy Contents: Mathematical Models and the Modeling CycleGrowth of a Population:Evolution and EquilibriumStability and BifurcationInteracting Populations:Linear InteractionsNonlinear Autonomous InteractionsHIV Dynamics and Drug TreatmentsIndex Theory, Bistability and FeedbackOptimization:The Economics of GrowthOptimization over a Planning PeriodModifications of the Basic ProblemBoundary Value Problems are More ComplexConstraints and Control:"Do Your Best" and the Maximum PrincipleChlamydia TrachomatisGenetic Instability and CarcinogenesisMathematical Modeling RevisitedAppendices:First Order ODEBasic Numerical MethodsAssignments Readership: Undergraduates in mathematical biology, mathematical modeling of dynamical systems, optimization and control, viral dynamics (infectious diseases), oncology.