Perspectives on Logics for Data-Driven Reasoning
暫譯: 數據驅動推理的邏輯觀點

Hosni, Hykel, Landes, Jürgen

Perspectives on Logics for Data-Driven Reasoning
  • 出版商: Springer
  • 出版日期: 2025-01-22
  • 售價: $5,230
  • 貴賓價: 9.5 折 $4,969
  • 語言: 英文
  • 頁數: 207
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 303177891X
  • ISBN-13: 9783031778919

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

這本書呼籲重新思考邏輯作為科學推理的核心方法工具，特別是在對數據中心科學日益重視的背景下。為此，它提供了邏輯在充分利用當前機會方面的最新呈現，同時明確指出數據驅動的科學研究時代所帶來的主要挑戰。

特別關注以下四個核心領域和應用：與相關性推理（醫學、生命科學應用）；統計推斷的邏輯（機器學習及其社會應用）；證據推理（定義良好證據）；因果推理（法醫推理）。

本書匯集了關鍵邏輯學家、方法論者和科學家的貢獻。這種多學科的視角對於對數據驅動科學感興趣的科學家和邏輯學家都有所裨益。科學家們接觸到超越傳統的邏輯，因而能夠應用於數據推理；邏輯學家則有機會專注於他們的方法和技術在緊迫科學問題上的潛在應用。因此，這本書對於從事數據中心科學的科學家和邏輯學家都具有興趣。

作者簡介

Hykel Hosni is professor of Logic at the Department of Philosophy at University of Milan, and currently head of the Logic, Uncertainty, Computation, and Information (LUCI) Lab. He contributed to the logical foundations of reasoning and decision-making under uncertainty. His main current interest lies with the logical foundation of data-intensive and AI-driven science.

Jürgen Landes is a researcher Munich Center for Mathematical Philosophy at the LMU Munich. His work spans a wide variety of problems, approaches and techniques related to uncertain inference. In particular, he contributed to Pure Inductive Logic, the Principle of Maximum Entropy, general Bayesian inference and Bayesian inference in medicine.

作者簡介(中文翻譯)

Hykel Hosni 是米蘭大學哲學系的邏輯學教授，目前擔任邏輯、不確定性、計算與資訊（Logic, Uncertainty, Computation, and Information, LUCI）實驗室的負責人。他對於不確定性下的推理與決策的邏輯基礎做出了貢獻。他目前的主要興趣在於數據密集型和人工智慧驅動科學的邏輯基礎。

Jürgen Landes 是慕尼黑大學數學哲學中心的研究員。他的研究涵蓋了與不確定推理相關的各種問題、方法和技術。特別是，他對純粹歸納邏輯、最大熵原則、一般貝葉斯推理以及醫學中的貝葉斯推理做出了貢獻。

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