Neuro Symbolic Artificial Intelligence The State Of The Art

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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 : 54,8 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 : 49,5 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.

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
Page : 490 pages
File Size : 53,7 Mb
Release : 2007-08-19
Category : Computers
ISBN : 9780585295992

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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.

Perspectives of Neural-Symbolic Integration

Barbara Hammer,Pascal Hitzler
Perspectives of Neural Symbolic Integration Book PDF

Author : Barbara Hammer,Pascal Hitzler
Publisher : Springer
Page : 0 pages
File Size : 48,8 Mb
Release : 2010-11-25
Category : Mathematics
ISBN : 3642093221

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Perspectives of Neural-Symbolic Integration by Barbara Hammer,Pascal Hitzler Pdf

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.

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 : 46,8 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.

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 : 55,8 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.

Hybrid Neural Systems

Stefan Wermter,Ron Sun
Hybrid Neural Systems Book PDF

Author : Stefan Wermter,Ron Sun
Publisher : Springer
Page : 408 pages
File Size : 41,6 Mb
Release : 2006-12-30
Category : Medical
ISBN : 9783540464174

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Hybrid Neural Systems by Stefan Wermter,Ron Sun Pdf

Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.

ECAI 2023

K. Gal,A. Nowé,G.J. Nalepa
ECAI 2023 Book PDF

Author : K. Gal,A. Nowé,G.J. Nalepa
Publisher : IOS Press
Page : 3328 pages
File Size : 53,9 Mb
Release : 2023-10-18
Category : Computers
ISBN : 9781643684376

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ECAI 2023 by K. Gal,A. Nowé,G.J. Nalepa Pdf

Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.

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 : 46,5 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.

Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications

Alonso, Eduardo,Mondrag¢n, Esther
Computational Neuroscience for Advancing Artificial Intelligence Models Methods and Applications Book PDF

Author : Alonso, Eduardo,Mondrag¢n, Esther
Publisher : IGI Global
Page : 396 pages
File Size : 42,6 Mb
Release : 2010-11-30
Category : Computers
ISBN : 9781609600235

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Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications by Alonso, Eduardo,Mondrag¢n, Esther Pdf

"This book argues that computational models in behavioral neuroscience must be taken with caution, and advocates for the study of mathematical models of existing theories as complementary to neuro-psychological models and computational models"--

Toward Robots That Reason: Logic, Probability & Causal Laws

Vaishak Belle
Toward Robots That Reason Logic Probability Causal Laws Book PDF

Author : Vaishak Belle
Publisher : Springer Nature
Page : 201 pages
File Size : 48,5 Mb
Release : 2023-02-20
Category : Computers
ISBN : 9783031210037

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Toward Robots That Reason: Logic, Probability & Causal Laws by Vaishak Belle Pdf

This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge.

Advances in Visual Computing

George Bebis,Golnaz Ghiasi,Yi Fang,Andrei Sharf,Yue Dong,Chris Weaver,Zhicheng Leo,Joseph J. LaViola Jr.,Luv Kohli
Advances in Visual Computing Book PDF

Author : George Bebis,Golnaz Ghiasi,Yi Fang,Andrei Sharf,Yue Dong,Chris Weaver,Zhicheng Leo,Joseph J. LaViola Jr.,Luv Kohli
Publisher : Springer Nature
Page : 506 pages
File Size : 44,5 Mb
Release : 2024-01-03
Category : Computers
ISBN : 9783031479663

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Advances in Visual Computing by George Bebis,Golnaz Ghiasi,Yi Fang,Andrei Sharf,Yue Dong,Chris Weaver,Zhicheng Leo,Joseph J. LaViola Jr.,Luv Kohli Pdf

This volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA. The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as: Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture. Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.

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 : 47,6 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.

NEUROSYMBOLIC PROGRAMMING

SWARAT CHAUDHURI; KEVIN ELLIS; OLEKSANDR POLOZOV,Swarat Chaudhuri,Kevin Ellis,Rishabh Singh,Armando Solar-Lezama,Yishong Yue
NEUROSYMBOLIC PROGRAMMING Book PDF

Author : SWARAT CHAUDHURI; KEVIN ELLIS; OLEKSANDR POLOZOV,Swarat Chaudhuri,Kevin Ellis,Rishabh Singh,Armando Solar-Lezama,Yishong Yue
Publisher : Unknown
Page : 128 pages
File Size : 41,6 Mb
Release : 2021
Category : Computer programming
ISBN : 1680839357

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NEUROSYMBOLIC PROGRAMMING by SWARAT CHAUDHURI; KEVIN ELLIS; OLEKSANDR POLOZOV,Swarat Chaudhuri,Kevin Ellis,Rishabh Singh,Armando Solar-Lezama,Yishong Yue Pdf

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.

Logics in Artificial Intelligence

Sarah Gaggl,Maria Vanina Martinez,Magdalena Ortiz
Logics in Artificial Intelligence Book PDF

Author : Sarah Gaggl,Maria Vanina Martinez,Magdalena Ortiz
Publisher : Springer Nature
Page : 834 pages
File Size : 40,6 Mb
Release : 2023-10-25
Category : Computers
ISBN : 9783031436192

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Logics in Artificial Intelligence by Sarah Gaggl,Maria Vanina Martinez,Magdalena Ortiz Pdf

This book constitutes proceedings of the 18th European Conference on Logics in Artificial Intelligence, JELIA 2023, held in Dresden, Germany, in September 2023. The 41 full papers and 11 short papers included in this volume were carefully reviewed and selected from 111 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).