Symbolic Artificial Intelligence

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Neuro-Symbolic Artificial Intelligence: The State of the Art

P. Hitzler
Neuro Symbolic Artificial Intelligence The State of the Art Book PDF

Author : P. Hitzler
Publisher : IOS Press
Page : 410 pages
File Size : 44,6 Mb
Release : 2022-01-19
Category : Computers
ISBN : 9781643682457

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Neuro-Symbolic Artificial Intelligence: The State of the Art by P. Hitzler Pdf

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.

Compendium of Neurosymbolic Artificial Intelligence

P. Hitzler,M.K. Sarker,A. Eberhart
Compendium of Neurosymbolic Artificial Intelligence Book PDF

Author : P. Hitzler,M.K. Sarker,A. Eberhart
Publisher : IOS Press
Page : 706 pages
File Size : 42,8 Mb
Release : 2023-08-04
Category : Computers
ISBN : 9781643684079

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Compendium of Neurosymbolic Artificial Intelligence by P. Hitzler,M.K. Sarker,A. Eberhart Pdf

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.

Neural-Symbolic Learning Systems

Artur S. d'Avila Garcez,Krysia B. Broda,Dov M. Gabbay
Neural Symbolic Learning Systems Book PDF

Author : Artur S. d'Avila Garcez,Krysia B. Broda,Dov M. Gabbay
Publisher : Springer Science & Business Media
Page : 276 pages
File Size : 45,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447102113

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Neural-Symbolic Learning Systems by Artur S. d'Avila Garcez,Krysia B. Broda,Dov M. Gabbay Pdf

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.

Symbolic Artificial Intelligence

Fouad Sabry
Symbolic Artificial Intelligence Book PDF

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
Page : 140 pages
File Size : 52,8 Mb
Release : 2023-07-03
Category : Computers
ISBN : PKEY:6610000473328

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Symbolic Artificial Intelligence by Fouad Sabry Pdf

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.

Common Sense, the Turing Test, and the Quest for Real AI

Hector J. Levesque
Common Sense the Turing Test and the Quest for Real AI Book PDF

Author : Hector J. Levesque
Publisher : MIT Press
Page : 190 pages
File Size : 40,9 Mb
Release : 2018-03-09
Category : Computers
ISBN : 9780262535205

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Common Sense, the Turing Test, and the Quest for Real AI by Hector J. Levesque Pdf

What artificial intelligence can tell us about the mind and intelligent behavior. What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to “good old fashioned artificial intelligence,” which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns—as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk. Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence—the Winograd Schema Test, developed by Levesque and his colleagues. “If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it,” he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.

Artificial Intelligence with Common Lisp

James L. Noyes
Artificial Intelligence with Common Lisp Book PDF

Author : James L. Noyes
Publisher : Jones & Bartlett Learning
Page : 644 pages
File Size : 45,8 Mb
Release : 1992
Category : Computers
ISBN : 0669194735

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Artificial Intelligence with Common Lisp by James L. Noyes Pdf

[The book] provides a balanced survey of the fundamentals of artificial intelligence, emphasizing the relationship between symbolic and numeric processing. The text is structured around an innovative, interactive combination of LISP programming and AI; it uses the constructs of the programming language to help readers understand the array of artificial intelligence concepts presented. After an overview of the field of artificial intelligence, the text presents the fundamentals of LISP, explaining the language's features in more detail than any other AI text. Common Lisp is then used consistently, in both programming exercises and plentiful examples of actual AI code.- Back cover This text is intended to provide an introduction to both AI and LISp for those having a background in computer science and mathematics. -Pref.

Neuro-Symbolic AI

Alexiei Dingli,David Farrugia
Neuro Symbolic AI Book PDF

Author : Alexiei Dingli,David Farrugia
Publisher : Packt Publishing Ltd
Page : 196 pages
File Size : 47,6 Mb
Release : 2023-05-31
Category : Computers
ISBN : 9781804616956

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Neuro-Symbolic AI by Alexiei Dingli,David Farrugia Pdf

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.

Fundamentals of the New Artificial Intelligence

Toshinori Munakata
Fundamentals of the New Artificial Intelligence Book PDF

Author : Toshinori Munakata
Publisher : Springer Science & Business Media
Page : 266 pages
File Size : 45,8 Mb
Release : 2008-01-01
Category : Computers
ISBN : 9781846288395

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Fundamentals of the New Artificial Intelligence by Toshinori Munakata Pdf

The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.

Neural-Symbolic Cognitive Reasoning

Artur S. D'Avila Garcez,Luís C. Lamb,Dov M. Gabbay
Neural Symbolic Cognitive Reasoning Book PDF

Author : Artur S. D'Avila Garcez,Luís C. Lamb,Dov M. Gabbay
Publisher : Springer Science & Business Media
Page : 200 pages
File Size : 55,9 Mb
Release : 2009
Category : Computers
ISBN : 9783540732457

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Neural-Symbolic Cognitive Reasoning by Artur S. D'Avila Garcez,Luís C. Lamb,Dov M. Gabbay Pdf

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.

A Compendium of Machine Learning: Symbolic machine learning

Garry Briscoe,Terry Caelli
A Compendium of Machine Learning Symbolic machine learning Book PDF

Author : Garry Briscoe,Terry Caelli
Publisher : Intellect (UK)
Page : 386 pages
File Size : 53,7 Mb
Release : 1996
Category : Computers
ISBN : UOM:39015037491555

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A Compendium of Machine Learning: Symbolic machine learning by Garry Briscoe,Terry Caelli Pdf

Machine learning is a relatively new branch of artificial intelligence. The field has undergone a significant period of growth in the 1990s, with many new areas of research and development being explored.

Computational Architectures Integrating Neural and Symbolic Processes

Ron Sun,Lawrence A. Bookman
Computational Architectures Integrating Neural and Symbolic Processes Book PDF

Author : Ron Sun,Lawrence A. Bookman
Publisher : Springer Science & Business Media
Page : 490 pages
File Size : 53,9 Mb
Release : 1994-11-30
Category : Computers
ISBN : 9780792395171

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Computational Architectures Integrating Neural and Symbolic Processes by Ron Sun,Lawrence A. Bookman Pdf

Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently emerging body of research. With the reemergence of neural networks in the 1980s with their emphasis on overcoming some of the limitations of symbolic AI, there is clearly a need to support some form of high-level symbolic processing in connectionist networks. As argued by many researchers, on both the symbolic AI and connectionist sides, many cognitive tasks, e.g. language understanding and common sense reasoning, seem to require high-level symbolic capabilities. How these capabilities are realized in connectionist networks is a difficult question and it constitutes the focus of this book. Computational Architectures Integrating Neural and Symbolic Processes addresses the underlying architectural aspects of the integration of neural and symbolic processes. In order to provide a basis for a deeper understanding of existing divergent approaches and provide insight for further developments in this field, this book presents: (1) an examination of specific architectures (grouped together according to their approaches), their strengths and weaknesses, why they work, and what they predict, and (2) a critique/comparison of these approaches. Computational Architectures Integrating Neural and Symbolic Processes is of interest to researchers, graduate students, and interested laymen, in areas such as cognitive science, artificial intelligence, computer science, cognitive psychology, and neurocomputing, in keeping up-to-date with the newest research trends. It is a comprehensive, in-depth introduction to this new emerging field.

Artificial Intelligence

Melanie Mitchell
Artificial Intelligence Book PDF

Author : Melanie Mitchell
Publisher : Farrar, Straus and Giroux
Page : 336 pages
File Size : 54,5 Mb
Release : 2019-10-15
Category : Computers
ISBN : 9780374715236

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Artificial Intelligence by Melanie Mitchell Pdf

Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

Artificial Intelligence

John Haugeland
Artificial Intelligence Book PDF

Author : John Haugeland
Publisher : MIT Press
Page : 306 pages
File Size : 40,5 Mb
Release : 1989-01-06
Category : Psychology
ISBN : 0262580950

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Artificial Intelligence by John Haugeland Pdf

"Machines who think—how utterly preposterous," huff beleaguered humanists, defending their dwindling turf. "Artificial Intelligence—it's here and about to surpass our own," crow techno-visionaries, proclaiming dominion. It's so simple and obvious, each side maintains, only a fanatic could disagree. Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are "radically the same," provides the central theme for his illuminating and provocative book about this exciting new field. After a brief but revealing digression in intellectual history, Haugeland systematically tackles such basic questions as: What is a computer really? How can a physical object "mean" anything? What are the options for computational organization? and What structures have been proposed and tried as actual scientific models for intelligence? In a concluding chapter he takes up several outstanding problems and puzzles—including intelligence in action, imagery, feelings and personality—and their enigmatic prospects for solution.

Introduction to Artificial Intelligence

Mariusz Flasiński
Introduction to Artificial Intelligence Book PDF

Author : Mariusz Flasiński
Publisher : Springer
Page : 321 pages
File Size : 53,5 Mb
Release : 2016-08-31
Category : Computers
ISBN : 9783319400228

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Introduction to Artificial Intelligence by Mariusz Flasiński Pdf

In the chapters in Part I of this textbook the author introduces the fundamental ideas of artificial intelligence and computational intelligence. In Part II he explains key AI methods such as search, evolutionary computing, logic-based reasoning, knowledge representation, rule-based systems, pattern recognition, neural networks, and cognitive architectures. Finally, in Part III, he expands the context to discuss theories of intelligence in philosophy and psychology, key applications of AI systems, and the likely future of artificial intelligence. A key feature of the author's approach is historical and biographical footnotes, stressing the multidisciplinary character of the field and its pioneers. The book is appropriate for advanced undergraduate and graduate courses in computer science, engineering, and other applied sciences, and the appendices offer short formal, mathematical models and notes to support the reader.

Neuro Symbolic Reasoning and Learning

Paulo Shakarian,Chitta Baral,Gerardo I. Simari,Bowen Xi,Lahari Pokala
Neuro Symbolic Reasoning and Learning Book PDF

Author : Paulo Shakarian,Chitta Baral,Gerardo I. Simari,Bowen Xi,Lahari Pokala
Publisher : Springer
Page : 0 pages
File Size : 45,6 Mb
Release : 2023-09-10
Category : Computers
ISBN : 3031391780

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Neuro Symbolic Reasoning and Learning by Paulo Shakarian,Chitta Baral,Gerardo I. Simari,Bowen Xi,Lahari Pokala Pdf

This book provides a broad overview of the key results and frameworks for various NSAO 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.