Neuro Symbolic Reasoning And Learning
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Neuro Symbolic Reasoning And Learning
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Author : Paulo Shakarian
language : en
Publisher: Springer Nature
Release Date : 2023-10-15
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 2023-10-15 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.
Neural Symbolic Learning Systems
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Author : Artur S. d'Avila Garcez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Symbolic Learning Systems 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 2012-12-06 with Computers categories.
Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.
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.
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 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.
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.
Neurosymbolic Programming
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Author : SWARAT CHAUDHURI; KEVIN ELLIS; OLEKSANDR POLOZOV
language : en
Publisher:
Release Date : 2021
Neurosymbolic Programming written by SWARAT CHAUDHURI; KEVIN ELLIS; OLEKSANDR POLOZOV and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computer programming categories.
Neurosymbolic programming is an emerging area that bridges the areas of deep learning and program synthesis. As in classical machine learning, the goal is to learn functions from data. However, these functions are represented as programs that can use neural modules in addition to symbolic primitives and are induced using a combination of symbolic search and gradient-based optimization. Neurosymbolic programming can offer multiple advantages over end-to-end deep learning. Programs can sometimes naturally represent long-horizon, procedural tasks that are difficult to perform using deep networks. Neurosymbolic representations are also, commonly, easier to interpret and formally verify than neural networks. The restrictions of a programming language can serve as a form of regularization and lead to more generalizable and data-efficient learning. Compositional programming abstractions can also be a natural way of reusing learned modules across learning tasks. In this monograph, the authors illustrate these potential benefits with concrete examples from recent work on neurosymbolic programming. They also categorize the main ways in which symbolic and neural learning techniques come together in this area and conclude with a discussion of the open technical challenges in the field. The comprehensive review of neurosymbolic programming introduces the reader to the topic and provides an insightful treatise on an increasingly important topic at the intersection of programming languages and machine learning. p learning or verification.
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.
Conceptual Structures
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Author : John F. Sowa
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1984
Conceptual Structures written by John F. Sowa and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Computers categories.
"This book combines the AI and cognitive sciences approaches. In combing insights from each of the separate fields, the book gives a unified view of knowledge representation." -- Preface.
Perspectives Of Neural Symbolic Integration
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Author : Barbara Hammer
language : en
Publisher: Springer
Release Date : 2007-08-14
Perspectives Of Neural Symbolic Integration written by Barbara Hammer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-14 with Technology & Engineering categories.
When it comes to robotics and bioinformatics, the Holy Grail everyone is seeking is how to dovetail logic-based inference and statistical machine learning. This volume offers some possible solutions to this eternal problem. Edited with flair and sensitivity by Hammer and Hitzler, the book contains state-of-the-art contributions in neural-symbolic integration, covering `loose' coupling by means of structure kernels or recursive models as well as `strong' coupling of logic and neural networks.