Neuro Symbolic Artificial Intelligence
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Neuro Symbolic Artificial Intelligence The State Of The Art
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Author : P. Hitzler
language : en
Publisher: IOS Press
Release Date : 2022-01-19
Neuro Symbolic Artificial Intelligence The State Of The Art written by P. Hitzler and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-19 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.
Neuro Symbolic Artificial Intelligence
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Author : Bikram Pratim Bhuyan
language : en
Publisher: Springer Nature
Release Date : 2024-12-22
Neuro Symbolic Artificial Intelligence written by Bikram Pratim Bhuyan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-22 with Computers categories.
This book highlights and attempts to fill a crucial gap in the existing literature by providing a comprehensive exploration of the emerging field of neuro-symbolic AI. It introduces the concept of neuro-symbolic AI, highlighting its fusion of symbolic reasoning and machine learning. The book covers symbolic AI and knowledge representation, neural networks and deep learning, neuro-symbolic integration approaches, reasoning and inference techniques, applications in healthcare and robotics, as well as challenges and future directions. By combining the power of symbolic logic and knowledge representation with the flexibility of neural networks, neuro-symbolic AI offers the potential for more interpretable and trustworthy AI systems. This book is a valuable resource for researchers, practitioners, and students interested in understanding and applying neuro-symbolic AI.
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.
Neuro Symbolic Ai
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Author : Alexiei Dingli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-31
Neuro Symbolic Ai written by Alexiei Dingli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Computers categories.
Explore the inner workings of AI along with its limitations and future developments and create your first transparent and trustworthy neuro-symbolic AI system Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand symbolic and statistical techniques through examples and detailed explanations Explore the potential of neuro-symbolic AI for future developments using case studies Discover the benefits of combining symbolic AI with modern neural networks to build transparent and high-performance AI solutions Book Description Neuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks. This book provides an overview of AI and its inner mechanics, covering both symbolic and neural network approaches. You'll begin by exploring the decline of symbolic AI and the recent neural network revolution, as well as their limitations. The book then delves into the importance of building trustworthy and transparent AI solutions using explainable AI techniques. As you advance, you'll explore the emerging field of neuro-symbolic AI, which combines symbolic AI and modern neural networks to improve performance and transparency. You'll also learn how to get started with neuro-symbolic AI using Python with the help of practical examples. In addition, the book covers the most promising technologies in the field, providing insights into the future of AI. Upon completing this book, you will acquire a profound comprehension of neuro-symbolic AI and its practical implications. Additionally, you will cultivate the essential abilities to conceptualize, design, and execute neuro-symbolic AI solutions. What you will learn Gain an understanding of the intuition behind neuro-symbolic AI Determine the correct uses that can benefit from neuro-symbolic AI Differentiate between types of explainable AI techniques Think about, design, and implement neuro-symbolic AI solutions Create and fine-tune your first neuro-symbolic AI system Explore the advantages of fusing symbolic AI with modern neural networks in neuro-symbolic AI systems Who this book is for This book is ideal for data scientists, machine learning engineers, and AI enthusiasts who want to explore the emerging field of neuro-symbolic AI and discover how to build transparent and trustworthy AI solutions. A basic understanding of AI concepts and familiarity with Python programming are needed to make the most of this book.
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.
Compendium Of Neurosymbolic Artificial Intelligence
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Author : P. Hitzler
language : en
Publisher: IOS Press
Release Date : 2023-08-04
Compendium Of Neurosymbolic Artificial Intelligence written by P. Hitzler and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-04 with Computers categories.
If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches to AI; symbolic reasoning and neural or connectionist approaches such as Deep Learning. The quest to unite these two types of AI has led to the development of many innovative techniques which extend the boundaries of both disciplines. This book, Compendium of Neurosymbolic Artificial Intelligence, presents 30 invited papers which explore various approaches to defining and developing a successful system to combine these two methods. Each strategy has clear advantages and disadvantages, with the aim of most being to find some useful middle ground between the rigid transparency of symbolic systems and the more flexible yet highly opaque neural applications. The papers are organized by theme, with the first four being overviews or surveys of the field. These are followed by papers covering neurosymbolic reasoning; neurosymbolic architectures; various aspects of Deep Learning; and finally two chapters on natural language processing. All papers were reviewed internally before publication. The book is intended to follow and extend the work of the previous book, Neuro-symbolic artificial intelligence: The state of the art (IOS Press; 2021) which laid out the breadth of the field at that time. Neurosymbolic AI is a young field which is still being actively defined and explored, and this book will be of interest to those working in AI research and development.
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.
The Self Assembling Brain
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Author : Peter Robin Hiesinger
language : en
Publisher: Princeton University Press
Release Date : 2021-05-04
The Self Assembling Brain written by Peter Robin Hiesinger and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Computers categories.
"In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"--
Artificial Intelligence For Cognitive Systems Deep Learning Neuro Symbolic Integration And Human Centric Intelligence
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Author : Samit Shivadekar
language : en
Publisher: Deep Science Publishing
Release Date : 2025-06-30
Artificial Intelligence For Cognitive Systems Deep Learning Neuro Symbolic Integration And Human Centric Intelligence written by Samit Shivadekar and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
Artificial intelligence quickly changed from a theory to a practical power - it spreads through every part of modern life. As people go from specific uses to more general kinds of intelligence, they must face a main change. This change involves what machines do and how people think about intelligence. The book, Cognitive AI - From Deep Learning to Artificial General Intelligence, looks at that change. This writing serves a wide, serious group of people - it is for graduate students and researchers in artificial intelligence and cognitive science. Educators along with industry workers also read this to get a better grasp of the path from current AI systems to future cognitive architectures. We do not just list technologies. We deal with the concepts, morals, technical issues as well as societal problems that sit at the core of creating machines that think. The chapters lay out this story bit by bit; they start with basic learning systems. They move to cognitive modeling and designs. The book finishes with important questions about governance, combining fields along with how people will work in the future. Throughout the text, the reader learns about current subjects. Some of these are large language models, explaining how systems work, reasoning with symbols plus networks, the safety of general artificial intelligence, and people working with machines. I appreciate the researchers, collaborators along with students who inspired this work. The growing group of thinkers also recognizes that making intelligent systems requires scientific exactness and philosophical thought. My hope is that this book guides plus starts talks for anyone who wants AI to develop responsibly and creatively.
Symbolic Artificial Intelligence
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-07-03
Symbolic Artificial Intelligence written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-03 with Computers categories.
What Is Symbolic Artificial Intelligence In the field of artificial intelligence, the term "symbolic artificial intelligence" refers to the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of issues, logic, and search. In other words, symbolic artificial intelligence is the name for the collection of all methods in artificial intelligence research. Symbolic AI created applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. It utilized techniques such as logic programming, production rules, and semantic nets and frames. The paradigm of symbolic artificial intelligence led to the development of important ideas in the fields of search, symbolic programming languages, agents, multi-agent systems, the semantic web, as well as the benefits and drawbacks of formal knowledge and reasoning systems. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Symbolic Artificial Intelligence Chapter 2: Artificial Intelligence Chapter 3: Expert System Chapter 4: Knowledge Representation and Reasoning Chapter 5: Neats and Scruffies Chapter 6: Dendral Chapter 7: Computational Cognition Chapter 8: Physical Symbol System Chapter 9: History of Artificial Intelligence Chapter 10: Hybrid Intelligent System (II) Answering the public top questions about symbolic artificial intelligence. (III) Real world examples for the usage of symbolic artificial intelligence in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of symbolic artificial intelligence' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of symbolic artificial intelligence.