The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science.
Cuprins
Modelling and Inferring in Science.- On ‘The Unreasonable Effectiveness of Mathematics in the Natural Sciences’.- Fast and Frugal Heuristics at Research Frontiers.- Scientific Realism, the Semantic View and Evolutionary Biology.- Models of the Skies.- Models of Science and Models in Science.- Mechanistic Models and Modeling Disorders.- Chaos and Stochastic Models in Physics.- Ways of Advancing Knowledge. A Lesson from Knot Theory and Topology.- Models, Idealisations, and Realist Commitments.- Modelling Non-Empirical Confirmation.- Mathematics as an Empirical Phenomenon, Subject to Modeling.- Scientific Models Are Distributed and Never Abstract. A Naturalistic Perspective.- The Use of Models in Petroleum and Natural Gas Engineering.
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