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Perspectives on Logics for Data-driven Reasoning

Hykel Hosni (Hrsg.), Jürgen Landes (Hrsg.)

PDF
ca. 139,09

Springer Nature Switzerland img Link Publisher

Geisteswissenschaften, Kunst, Musik / Allgemeines, Lexika

Beschreibung

This book calls for a rethinking of logic as the core methodological tool for scientific reasoning in the context of a steadily increasing emphasis on data-centered science. To do so it provides a state-of-the-art presentation of the role logic can have in making the most of the current opportunities while making explicit the key challenges opened up by the data-driven age of scientific research.

Particular attention is given to the following four core fields and applications: Reasoning with correlations (medical, life-science applications); logics for statistical inference (machine learning, and societal applications thereof); reasoning with evidence (defining good evidence); causal reasoning (forensic reasoning).

The book collects contributions from key logicians, methodologists and scientists. This multidisciplinary perspective benefits both scientists and logicians interested in data-driven science. Scientists are introduced to logics that go beyond classical and thus are applicable to reasoning with data; Logicians have a change to focus on the potential applications of their methods and techniques to pressing scientific problems. This book is, therefore, of interest to scientists and logicians working on data-centered science.

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Schlagwörter

Evidence and logic, Causal reasoning, Data-driven reasoning, Logics for statistical inference, Reasoning with evidence, Statistical inference, Data-centered science, Logic and data, Reasoning with correlation