Springer Handbook of Model-Based Science
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The handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in philosophy, the history of science, general epistemology, mathematics, cognitive and computer science, physics and life sciences, as well as engineering, architecture, and economics, this Handbook uses numerous diagrams, schemes and other visual representations to promote a better understanding of the concepts. This also makes it highly accessible to an audience of scholars and students with different scientific backgrounds. All in all, the Springer Handbook of Model-Based Science represents the definitive application-oriented reference guide to the interdisciplinary field of model-based reasoning.
“What [the editors] have created is more than a snapshot of a growing, sophisticated, multifaceted field: they provided a rich map (a model!) of a sprawling, genuinely interdisciplinary, eclectic, and endlessly fascinating nested series of domains of research.” (Prof. Otávio Bueno, University of Miami, Dept. of Philosophy & Editor-in-Chief Synthese)
“The diverse thoughtful and thought-provoking contributions reveal fascinating intricacies in model-based reasoning, the nuances of finding suitable representations (models) and the complexities of using them to draw inferences. The many insights in each contribution and in the section overviews cannot readily be summarized, they must be savored. They will be a continuing source of inspiration.” (Prof. Barbara Tversky, Stanford University and Columbia Teachers College)