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Titlebook: The Logic of Discovery; A Theory of the Rati Scott A. Kleiner Book 1993 Springer Science+Business Media B.V. 1993 access.artificial intelli

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書目名稱The Logic of Discovery
副標題A Theory of the Rati
編輯Scott A. Kleiner
視頻videohttp://file.papertrans.cn/914/913232/913232.mp4
叢書名稱Synthese Library
圖書封面Titlebook: The Logic of Discovery; A Theory of the Rati Scott A. Kleiner Book 1993 Springer Science+Business Media B.V. 1993 access.artificial intelli
描述Scientific research is viewed as a deliberate activity and thelogic of discovery consists of strategies and arguments whereby thebest objectives (questions) and optimal means for achieving theseobjectives (heuristics) are chosen. This book includes a discussionand some proposals regarding the way the logic of questions can beapplied to understanding scientific research and draws upon work inartificial intelligence in a discussion of heuristics and methods forappraising heuristics (metaheuristics). It also includes a discussionof a third source for scientific objectives and heuristics; episodesand examplars from the history of science and the history ofphilosophy..This book is written to be accessible to advanced students inphilosophy and to the scientific community. It is of interest tophilosophers of science, philosophers of biology, historians ofphysics, and historians of biology..
出版日期Book 1993
關(guān)鍵詞access; artificial intelligence; heuristics; history; history of literature; history of science; logic; met
版次1
doihttps://doi.org/10.1007/978-94-015-8216-2
isbn_softcover978-90-481-4297-2
isbn_ebook978-94-015-8216-2Series ISSN 0166-6991 Series E-ISSN 2542-8292
issn_series 0166-6991
copyrightSpringer Science+Business Media B.V. 1993
The information of publication is updating

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https://doi.org/10.1007/978-94-015-8216-2access; artificial intelligence; heuristics; history; history of literature; history of science; logic; met
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The Logic of Discovery978-94-015-8216-2Series ISSN 0166-6991 Series E-ISSN 2542-8292
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https://doi.org/10.1007/978-3-663-08032-9 function on the final performance of the proposed methods. The proposed methods demonstrated that some fitness functions like the accuracy rate can mislead the identification process of the relevant features in imbalanced datasets.
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