Perspectives on Logics for Data-driven Reasoning (Logic, Argumentation & Reasoning, 35) (Original PDF from Publisher)

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By Hykel Hosni, Jürgen Landes 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…

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By Hykel Hosni, Jürgen Landes

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.

Product Details

  • Publisher ‏ : ‎ Springer
  • Publication date ‏ : ‎ January 22, 2025
  • Language ‏ : ‎ English
  • ISBN-10 ‏ : ‎ 303177891X
  • ISBN-13 ‏ : ‎ 978-3031778919

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