01021nam a2200253 i 450099100093630970753620020507180147.0010529s1998 it ||| | ita b10778056-39ule_instLE01304552ExLDip.to Matematicaeng516.36AMS 55R25Carluccio, Anna Rita535521Geometria del fibrato sferico tangente. Tesi di laurea /laureanda Anna Rita Carluccio ; relat. Domenico PerroneLecce :Università degli studi. Facoltà di Scienze. Corso di laurea in Matematica,a.a. 1998-99Sphere bundlesPerrone, Domenico.b1077805602-04-1428-06-02991000936309707536LE013 TES 1998/99 CAR112013000127262le013-E0.00-l- 00000.i1087729028-06-02Geometria del fibrato sferico tangente. Tesi di laurea921734UNISALENTOle01301-01-01ma -itait 0104297nam 22006375 450 991074450830332120251009082300.09783031391798(print)3031391799(print)9783031391798303139179910.1007/978-3-031-39179-8(MiAaPQ)EBC30742315(Au-PeEL)EBL30742315(OCoLC)1397575687(DE-He213)978-3-031-39179-8(PPN)272736333(CKB)28222999100041(EXLCZ)992822299910004120230913d2023 u| 0engur|n#|||a|||atxtrdacontentcrdamediacrrdacarrierNeuro Symbolic Reasoning and Learning /by Paulo Shakarian, Chitta Baral, Gerardo I. Simari, Bowen Xi, Lahari Pokala1st ed. 2023.Cham :Springer Nature Switzerland :Imprint: Springer,2023.1 online resource (xii, 119 pages) illustrationsSpringerBriefs in Computer Science,2191-5776Print version: Shakarian, Paulo Neuro Symbolic Reasoning and Learning Cham : Springer,c2023 9783031391781 Includes bibliographical references.Chapter1 New Ideas in Neuro Symbolic Reasoning and Learning -- Chapter2 Brief Introduction to Propositional Logic and Predicate Calculus -- Chapter3 Fuzzy and Annotated Logic for Neuro Symbolic Artificial Intelligence -- Chapter4 LTN: Logic Tensor Networks -- Chapter5 Neuro Symbolic Reasoning with Ontological Networks -- Chapter6 LNN: Logical Neural Networks -- Chapter7 NeurASP -- Chapter8 Neuro Symbolic Learning with Differentiable Inductive Logic Programming -- Chapter9 Understanding SATNet: Constraint Learning and Symbol Grounding -- Chapter10 Neuro Symbolic AI for Sequential Decision Making -- Chapter11 Neuro Symbolic Applications.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 usage in various application areas. This book is designed for researchers and advanced-level students trying to understand the current landscape of NSAI research as well as those looking to apply NSAI research in areas such as natural language processing and visual question answering. Practitioners who specialize in employing machine learning and AI systems for operational use will find this book useful as well.SpringerBriefs in Computer Science,2191-5776Artificial intelligenceMachine learningArtificial IntelligenceMachine LearningArtificial intelligence.Machine learning.Artificial Intelligence.Machine Learning.006.31Shakarian Paulo791399Baral ChittaSimari Gerardo I.Xi BowenPokala LahariMiAaPQMiAaPQMiAaPQBOOK9910744508303321Neuro symbolic reasoning and learning3659084UNINA