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Titlebook: Neuro Symbolic Reasoning and Learning; Paulo Shakarian,Chitta Baral,Lahari Pokala Book 2023 The Editor(s) (if applicable) and The Author(s

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發(fā)表于 2025-3-21 17:55:05 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Neuro Symbolic Reasoning and Learning
編輯Paulo Shakarian,Chitta Baral,Lahari Pokala
視頻videohttp://file.papertrans.cn/664/663778/663778.mp4
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: Neuro Symbolic Reasoning and Learning;  Paulo Shakarian,Chitta Baral,Lahari Pokala Book 2023 The Editor(s) (if applicable) and The Author(s
描述.This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas.? This book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frameworks. This would include differential inductive logic programming, constraint learning and deep symbolic policy learning.? Additionally, application areas such a visual question answering and natural language processing are discussed as well as topics such as verification of neural networks and symbol grounding.? Detailed algorithmic descriptions, example logic programs, and an online supplement that includes instructional videos and slides provide thorough but concise coverage of this important area of AI...Neuro symbolic artificial intelligence (NSAI) encompasses the combination of deep neural networks with symbolic logic for reasoning and learning tasks.? NSAI frameworks are now capable of embedding priorknowledge in deep learning architectures, guiding the learning process with logical constraints, providing symbolic explainability, and using gradient-based approaches to learn logical statements.? Several approaches are seeing us
出版日期Book 2023
關(guān)鍵詞Artificial intelligence; Machine Learning; Deep Learning; Fuzzy Logic; Neural networks; Neuro symbolic ar
版次1
doihttps://doi.org/10.1007/978-3-031-39179-8
isbn_softcover978-3-031-39178-1
isbn_ebook978-3-031-39179-8Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/n/image/663778.jpg
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https://doi.org/10.1007/978-3-031-39179-8Artificial intelligence; Machine Learning; Deep Learning; Fuzzy Logic; Neural networks; Neuro symbolic ar
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Brief Introduction to Propositional Logic and Predicate Calculus,ehind propositional logic and predicate calculus (first order logic). We cover syntax, semantics, satisfiability relationships, consistency and entailment, quantifiers and grounding, as well as how logic relates to lattice theory and fixpoint operators.
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Neuro Symbolic Learning with Differentiable Inductive Logic Programming,wn as differentiable inductive logic programming (ILP), which combines concepts from ILP with a neural architecture to support gradient-based learning. Additionally, we also cover several other paradigms to learn logical structures in a neuro symbolic framework.
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Book 2023 book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frameworks. This would include differential inductive logic programming, constraint learning and deep symbolic policy learning.? Additionally, application areas such a visual question answering and natur
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