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Neural Symbolic Learning And Reasoning

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Neural Symbolic Cognitive Reasoning

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Author : Artur S. D'Avila Garcez
language : en
Publisher: Springer Science & Business Media
Release Date : 2009

Neural Symbolic Cognitive Reasoning written by Artur S. D'Avila Garcez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.

This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

Neural Symbolic Learning And Reasoning

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Author : Tarek R. Besold
language : en
Publisher: Springer Nature
Release Date : 2024-09-09

Neural Symbolic Learning And Reasoning written by Tarek R. Besold and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-09 with Computers categories.

This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.

Neural Symbolic Learning And Reasoning

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Author : Tarek R. Besold
language : en
Publisher: Springer Nature
Release Date : 2024-09-09

Neuro Symbolic Artificial Intelligence

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Author : Pascal Hitzler
language : en
Publisher:
Release Date : 2022

Neuro Symbolic Artificial Intelligence written by Pascal Hitzler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Computers categories.

Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. "Neuro" refers to the artificial neural networks prominent in machine learning, "symbolic" refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called "third wave" of AI is now bringing them together.This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be.Based on the editors' own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.

Artificial Intelligence

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Author : Charu C. Aggarwal
language : en
Publisher: Springer Nature
Release Date : 2021-07-16

Artificial Intelligence written by Charu C. Aggarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-16 with Computers categories.

This textbook covers the broader field of artificial intelligence. The chapters for this textbook span within three categories: Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5. Inductive Learning Methods: These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters~6 through 11. Integrating Reasoning and Learning: Chapters~11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence. The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.

Neuro Symbolic Reasoning And Learning

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Author : Paulo Shakarian
language : en
Publisher: Springer Nature
Release Date : 2023-09-13

Neuro Symbolic Reasoning And Learning written by Paulo Shakarian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-13 with Computers categories.

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 prior knowledge 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.

Fundamentals Of The New Artificial Intelligence

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Author : Toshinori Munakata
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-11-14

Fundamentals Of The New Artificial Intelligence written by Toshinori Munakata and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-11-14 with Computers categories.

A first course in AI, covering new technologies and their applications. With each topic, the book covers the most essential and widely employed material, particularly as it is used in real-world applications. The prerequisites are minimal: a basic understanding of computer science and mathematics is sufficient, making this suitable for undergraduates coming to the subject for the first time. Professor Munakata is a leading figure in this field and has given courses on this topic extensively. As a result, students and researchers will enjoy this authoritative introduction to the subject, with its emphasis on concise yet clear descriptions of the technical substance.

The Handbook On Reasoning Based Intelligent Systems

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Author : Kazumi Nakamatsu
language : en
Publisher: World Scientific
Release Date : 2013-01-18

The Handbook On Reasoning Based Intelligent Systems written by Kazumi Nakamatsu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Computers categories.

This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.

Mathematical Aspects Of Logic Programming Semantics

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Author : Pascal Hitzler
language : en
Publisher: CRC Press
Release Date : 2016-04-19

Mathematical Aspects Of Logic Programming Semantics written by Pascal Hitzler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Computers categories.

Covering the authors' own state-of-the-art research results, this book presents a rigorous, modern account of the mathematical methods and tools required for the semantic analysis of logic programs. It significantly extends the tools and methods from traditional order theory to include nonconventional methods from mathematical analysis that depend on topology, domain theory, generalized distance functions, and associated fixed-point theory. The authors closely examine the interrelationships between various semantics as well as the integration of logic programming and connectionist systems/neural networks.

Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges

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Author : Ilaria Tiddi
language : en
Publisher:
Release Date : 2020

Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by Ilaria Tiddi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Artificial intelligence categories.

The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.

Neural Symbolic Learning And Reasoning

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