One of the most noticeable features of the Renaissance is what Jacob Burckhardt called the rise of the individual - in politics and religion, in its social life and in the arts, and in the mentality of Renaissance man, with his inclination to explore, to invent and to make new discoveries. Yet this characteristic is also very puzzling to modern people, who see that although the categories of art which depict particular people increased to a spectacular degree in a period when biography and portrait painting were among the most popular genres, and autobiography began to emerge as a genre in itself and painters began to produce self-portraits, an interest individuals is not necessarily the same thing as the more recent interest in the purely personal aspects of individuals. Literary and artistic traditions, social and ideological backgrounds, and the motives for the production of literature have changed profoundly: Renaissance biography and autobiography, portraiture and self-portraiture have little to do with their modern counterparts. Therefore this book stresses that the Renaissance is not predominantly a mirror of modernity, but rather a period of stimulating difference or alterity. The contributors to this collection of essays aim to create a better understanding of Renaissance biographies and portraits through the analysis and reconstruction of the traditions, contexts, backgrounds and circumstances of their production.

Individual-Based Models of Cultural Evolution shows readers how to create individual-based models of cultural evolution using the programming language R. The field of cultural evolution has emerged in the last few decades as a thriving, interdisciplinary effort to understand cultural change and cultural diversity within an evolutionary framework and using evolutionary tools, concepts, and methods. Given its roots in evolutionary biology, much of cultural evolution is grounded in, or inspired by, formal models. Yet many researchers interested in cultural evolution come from backgrounds that lack training in formal modelling, such as psychology, anthropology or archaeology. This book addresses that gap. It provides example code in R for readers to run their own models, moving from very simple models of the basic processes of cultural evolution, such as biased transmission and cultural mutation, to more advanced topics such as the evolution of social learning, demographic effects, and social network analysis. Features of this book: Recreates existing models in the literature to show how these were created and to enable readers to have a better understanding of their significance and how to apply them to their own research questions Provides full R code to realize models and analyse and plot outputs, with line-by-line analysis Requires no previous knowledge of the field of cultural evolution, and only very basic programming knowledge This is an essential resource for researchers and students interested in cultural evolution, including disciplines such as psychology, anthropology, archaeology, and biology as well as sociology and digital humanities.

Recent technological advances in single-cell microbiology, using flow cytometry, microfluidics, x-ray fluorescence microprobes, and single-cell -omics, allow for the observation of individuals within populations. Simultaneously, individual-based models (or more generally agent-based models) allow for individual microbes to be simulated. Bridging these techniques forms the foundation of individual-based ecology of microbes (µIBE). µIBE has elucidated genetic and phenotypic heterogeneity that has important consequences for a number of human interests, including antibiotic or biocide resistance, the productivity and stability of industrial fermentations, the efficacy of food preservatives, and the potential of pathogens to cause disease. Individual-based models can help us to understand how these sets of traits of individual microbes influence the above. This eBook compiles all publications from a recent Research Topic in Frontiers in Microbiology. It features recent research where individual observational and/or modelling techniques are applied to gain unique insights into the ecology of microorganisms. The Research Topic “The Individual Microbe: Single-Cell Analysis and Agent-Based Modelling” arose from the 2016 @ASM conference of the same name hosted by the American Society for Microbiology at its headquarters in Washington, D.C. We are grateful to ASM for funding and hosting this conference.

Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call "individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is "theory"? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.

The book focusses on questions of individual and collective action, the emergence and dynamics of social norms and the feedback between individual behaviour and social phenomena. It discusses traditional modelling approaches to social norms and shows the usefulness of agent-based modelling for the study of these micro-macro interactions. Existing agent-based models of social norms are discussed and it is shown that so far too much priority has been given to parsimonious models and questions of the emergence of norms, with many aspects of social norms, such as norm-change, not being modelled. Juvenile delinquency, group radicalisation and moral decision making are used as case studies for agent-based models of collective action extending existing models by providing an embedding into social networks, social influence via argumentation and a causal action theory of moral decision making. The major contribution of the book is to highlight the multifaceted nature of the dynamics of social norms, consisting not only of emergence, and the importance of embedding of agent-based models into existing theory.

Until fairly recently, populations were handled as homogenized averages, which made modeling feasible but which ignored the essential fact that in any population there is a great variety of individuals of different ages, sizes, and degrees of fitness. Recently, because of the increased availability of affordable computer power, approaches have been developed which are able to recognize individual differences. Individual-based models are of great use in the areas of aquatic ecology, terrestrial ecology, landscape or physiological ecology, terrestrial ecology, landscape or physiological ecology, and agriculture. This book discusses which biological problems individual-based models can solve, as well as the models' inherent limitations. It explores likely future directions of theoretical development in these models, as well as currently feasible management applications and the best mathematical approaches and computer languages to use. The book also details specific applications to theory and management.

This thesis explores several interdisciplinary topics at the border of theoretical physics and biology, presenting results that demonstrate the power of methods from statistical physics when applied to neighbouring disciplines. From birth-death processes in switching environments to discussions on the meaning of quasi-potential landscapes in high-dimensional spaces, this thesis is a shining example of the efficacy of interdisciplinary research. The fields advanced in this work include game theory, the dynamics of cancer, and invasion of mutants in resident populations, as well as general contributions to the theory of stochastic processes. The background material provides an intuitive introduction to the theory and applications of stochastic population dynamics, and the use of techniques from statistical physics in their analysis. The thesis then builds on these foundations to address problems motivated by biological phenomena.