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Full Description
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.
Contents
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.
