Models and Inferences in Science [electronic resource] /
Ippoliti, Emiliano.editor.
Sterpetti, Fabio.editor.
Nickles, Tom.editor.
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.
Description based upon print version of record.
Includes bibliographical references at the end of each chapters.
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.
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.
Science
Engineering.
Logic, Symbolic and mathematical.
Genetic epistemology.
Philosophy of Science.
Computational Intelligence.
Mathematical Logic and Foundations.
Epistemology.
Theoretical, Mathematical and Computational Physics.