Handbook on Neurosymbolic AI and Knowledge Graphs

Neural approaches have traditionally excelled at perceptual tasks like pattern recognition, whereas symbolic frameworks have offered powerful methods for knowledge representation, logical inference, and interpretability, but the current AI landscape is increasingly defined by hybrid systems that blend these complementary paradigms. This is particularly relevant in the context of knowledge graphs (KGs), which serve as a bridge between symbolic logic and the subsymbolic world of deep learning.

The Handbook on Neurosymbolic AI and Knowledge Graphs deals with state-of-the-art neurosymbolic and KG-based AI, reflecting an ecosystem in which large language models, deep neural networks, and symbolic representations converge. It illustrates the progress that has been made, while also revealing emerging challenges in trustworthiness, interpretability, and scalability. The first four chapters are on the foundations of neural and symbolic AI. In the following chapters the authors explore the nuances of KG representation and embeddings, moving on to KG construction, integration, and quality, and covering challenges such as entity alignment, canonicalization, fusion, and the critical aspect of uncertainty management. Offering solutions that seamlessly combine symbolic logic with deep learning pipelines, the handbook deals with question answering, program synthesis, and dynamic KG methods, before moving on to the need to ensure transparency, accountability, and trust in systems operating on increasingly complex data. The final chapters demonstrate problem solving across news analytics, literary studies, life sciences, food computing, social media, and more.

This work offers a comprehensive overview of these intersecting fields and will be of interest to researchers and developers looking for a practical guide to building AI systems that are robust, transparent, and ethically grounded.

Editors: Hitzler, P., Dalal, A., Mahdavinejad, M.S., Norouzi, S.S.
Pages: 1118
Volume 400 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-578-6
ISBN online: 978-1-64368-579-3

Design Studies and Intelligence Engineering


Proceedings of DSIE 2024, Hangzhou, China, 21-22 December 2024

The technologies applied in design studies vary from basic theories to more application-based systems. Intelligent engineering also plays a significant role in design science, particularly in areas such as computer-aided industrial design, human-factor design, and greenhouse design, covering topics such as computational technologies, sensing technologies, and video detection from both a theoretical and an application perspective.

This book presents the proceedings of DSIE-2024, the 2024 International Symposium on Design Studies and Intelligence Engineering, held on 21 and 22 December 2024 in Hangzhou, China. The conference provided a platform for professionals and researchers from industry and academia to present and discuss recent advances in the fields of design studies and intelligent engineering, promoting cooperation between the industries and academics involved in these fields. A total of 498 submissions were received for the conference, all of which were carefully reviewed by 3 or 4 independent experts. The 157 papers presented at the conference and published here represent an acceptance rate of 32%. The papers are divided into 6 design categories: digital; emotional; human/machine interactive; innovative; intelligent; and sustainable, and subjects range from marketing innovations and detecting traffic anomalies to intelligent teaching resources and the use of AI in healthcare.

Covering a wide range of current innovations and encouraging cooperation between industry and academia, the book will be of interest to all those working in the converging fields of design studies and intelligent engineering.

Editors: Jain, L.C., Balas, V.E., Wu, Q., Shi, F.
Pages: 1563
Volume 405 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-586-1

Artificial Intelligence and Human-Computer Interaction


Proceedings of the 2nd International Conference (ArtInHCI 2024), Kunming, China, 25-27 October 2024

The importance of artificial intelligence (AI) to all our lives is now undeniable, and with interactions between humans, computers, and AI continuing to increase, this area has become the focus of growing interest.

This book presents the proceedings of ArtInHCI2024, the 2nd International Conference on Artificial Intelligence and Human-Computer Interaction, held as a hybrid event from 25 to 27 October 2024 in Kunming, China. The ArtInHCI conference series was conceived with the aim of promoting academic exchange within and across disciplines, addressing theoretical and practical challenges and advancing current understanding and application; a process which it is hoped will also serve to spread amity, establish connections and enable future collaboration. ArtInHCI2024 provided a platform for the discussion of a number of hot topics, including deep learning, artificial neural networks, computer vision and pattern recognition, and the conference focused on research challenges as well as those of application. A total of 191 submissions were received for the conference, and after initial screening, 142 were submitted to a rigorous, double blind peer review procedure based on relevance, writing skills, scientific quality and soundness, and contribution or practical implications. Following a final decision-making process, 93 of the papers were selected for presentation and publication here, an acceptance rate of 48.7%.

Covering a wide range of topics in the sphere of AI and human/computer interaction, the book will be of interest to all those working in the field.

Editors: Ye, Y., Zhou, H.
Pages: 868
Volume 404 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-583-0

Information Modelling and Knowledge Bases XXXVI

Information modeling and knowledge bases have become increasingly important for academic communities working with information systems, computer science, and artificial intelligence, and the volume and complexity and levels of abstraction, together with the size of databases and knowledge bases, continue to grow in parallel with the rising complexity of computational processes.

This book presents the proceedings of EJC 2024, the 34th international conference on Information Modelling and Knowledge Bases, held in Tokyo, Japan, from 10 to 14 June 2024. The EJC conference series aims to explore the progress in research communities with a common interest in understanding and solving problems on information modeling and knowledge bases and applying the results of research to practice by means of sharing scientific results and experiences achieved using innovative methods and systems in computer science and other disciplines. The selected papers published here cover many areas of information modeling and knowledge bases, including the theory of concepts, semantic computing, data mining, machine learning, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, natural language processing, software engineering, cross-cultural computing, environmental analysis, social computing, and many others. This latest edition of the conference also addressed the question of global & environmental AI for nature and society and asked whether System 2 can do everything that AI cannot do yet.

Offering a comprehensive overview of current developments, the book will be of interest to all those working in the field.

Editors: Kiyoki, Y., Sornlertlamvanich, V., Tropmann-Frick, M., Jaakkola, H., Yoshida, N.
Pages: 436
Volume 399 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-572-4

Safety-Aware Autonomous Systems


Preparing Robots for Life in the Real World

It is anticipated that real-world autonomous systems, such as AI-enabled robotic systems and intelligent transportation systems, will increasingly be deployed in real-world environments within the next few decades, precluding mundane human work, providing new services, and facilitating smarter and more flexible infrastructure in workplaces, public spaces, and homes. For such systems to be safe and secure, especially around people, it is important that they are explainable, predictable, and can deal with a real world that is constantly changing and only partially observable.

This book, Safety-Aware Autonomous Systems - Preparing Robots for Life in the Real World, investigates ways for autonomous systems to deal with dynamic and changing environments consistently and safely. The need for sound uncertainty management and the explicit uncertainty quantification required to provide probabilistic safety guarantees is explored, as is the runtime monitoring necessary to ensure safety in new situations. The realization of well-grounded prediction and classification uncertainty and the capacity to deal with unknown unknowns using anomaly detection are also interrogated. The degree of safety required can make it very challenging to reach useful levels of efficiency and effectiveness in safety-critical applications. To this end, a holistic perspective on agent motion in complex and dynamic environments is investigated. The book also discusses the leveraging of the synergies in well-founded formalized interactions, and the integration between learning, reasoning, and interaction.

Demonstrating efficient, effective, and safe capabilities for autonomous systems in safety-critical situations, the book will be of interest to all those working in the field.

Author: Tiger, M.
Pages: 330
Volume 402 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-565-6
ISBN online: 978-1-64368-566-3

Combining Concepts


Integrating Logical and Cognitive Theories of Concepts

What is a concept? Philosophy, cognitive science, psychology, logic, and AI have long been inquiring into this question. However, answers rarely converge.

The question of how humans represent and combine concepts has become increasingly relevant to AI. Despite advancements in Large Language Models and statistical models generally, the goal of developing formal representations of human thinking remains as crucial as ever. Cognitive models of human conceptualisation are of pivotal importance for AI and Knowledge Representation. Nevertheless, such models often lack proper formalisation, which makes it difficult to capture them precisely in computational systems. At the same time, the cognitive adequacy of computational systems is frequently overlooked in favour of better performance.

This book, Combining Concepts - Integrating Logical and Cognitive Theories of Concepts, bridges the gap between computational and cognitive models of concepts. The author explores the relationship between conceptual combination, the associated cognitive phenomena, and standard logical operators. The book introduces a representation of concepts motivated by the literature in cognitive psychology, combining ontological analysis, logical methods, and insights from statistical learning to offer a more cognitively grounded approach to modelling concepts and concept combination in Knowledge Representation and AI. It thus contributes to the development of hybrid AI modelling techniques, bridging learning and reasoning, and ensuring that they are theoretically sound, cognitively adequate, psychologically motivated, and practically applicable.

Offering a thorough exploration of concepts and concept combinations as they relate to current applications, the book will be of interest to all those working in the fields of AI and Knowledge Representation.

Author: Righetti, G.
Pages: 334
Volume 406 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-587-8
ISBN online: 978-1-64368-588-5

Digitalization and Management Innovation III


Proceedings of DMI 2024, Beijing, China, 25-27 October 2024

The rapid development of digital technologies has meant that management strategies and business models have also been transformed in recent years.

This book presents the proceedings of DMI2024, the 3rd International Conference on Digitalization and Management Innovation, held as a hybrid event from 25 to 27 October 2024 in Beijing, China. More than 100 participants from at least 10 countries took part in the conference, which provided a platform for the dissemination and discussion of innovative research and technological developments in the field of digitalization and management. A total of 293 submissions were received for the conference. Following a meticulous review process by program committee members, who carefully considered the breadth and depth of the research topics falling within the scope of DMI, 88 papers were selected for presentation and inclusion in this book; an acceptance rate of 30%. The book is divided into four parts: digitalization and business model, organizational behavior in digital transformation; management innovation and innovation management; special session on lifelong education; and interdisciplinary applications of digitalization and management innovation. Topics include innovation and business models, algorithms for management research and applications, and digital technology. Other contemporary topics such as leadership, the circular economy, green computing, human resource management, and online education management are also addressed.

Presenting original ideas and results of significant importance underpinned by rigorous methodologies, clear reasoning, and compelling evidence, the book will be of interest to all those working in the field.

Editor: Tallón-Ballesteros, A.J.
Pages: 858
Volume 403 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-582-3

Integrating Planning and Learning for Agents Acting in Unknown Environments

An Artificial Intelligence (AI) agent can perceive an environment through sensors and act in the environment through actuators. When performing tasks in a known environment, an agent knows what actions it can execute and how they affect the environment state, but when the environment is unknown, the agent needs to learn how the environment works to make good decisions for accomplishing tasks. In a real-world situation, an agent may have only low-level perceptions of the environment rather than the high-level representations required to make decisions by means of symbolic planning.

This book, Integrating Planning and Learning for Agents Acting in Unknown Environments proposes an architecture that integrates learning, planning, and acting. The author, Leonardo Lamanna, won the 2023 Marco Cadoli award, an annual award from the Italian Association for Artificial Intelligence (AIxIA) for the best doctoral thesis in the field of artificial intelligence, for this work. The approach combines data-driven learning methods for building an environment model with symbolic planning techniques for reasoning on the learned model, focusing on learning the model, either from continuous or symbolic observations. The problem of online learning the mapping between continuous perceptions and symbolic states is tackled, and symbolic planning techniques are exploited to enable an agent to autonomously gather relevant information online, which is required by learning methods to overcome some of the simplifying assumptions of symbolic planning. The effectiveness of the approach in simulated complex environments is shown experimentally and the applicability of the approach in real environments is demonstrated by conducting experiments on a real robot.

Outperforming state-of-the-art methods, the approach described in this book will be of interest to all those working in the field of AI and autonomous agents.

Author: Lamanna, L.
Pages: 132
Volume 401 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-570-0
ISBN online: 978-1-64368-571-7

Social Robots with AI: Prospects, Risks, and Responsible Methods


Proceedings of Robophilosophy 2024

The novel capacities of multimodal generative AI have suddenly brought us much closer to the longstanding vision of ubiquitous social robotics. Robots may soon become part of everyday life, performing many services as well or better than humans. We have entered a decisive phase in the robotic moment of human cultural history, and it is more urgent than ever that we determine “who we are and who we are willing to become” (Sherry Turkle).

This book presents the proceedings of RP2024, the sixth event in the biennial Robophilosophy Conference Series, held from 20 to 23 August 2024 in Aarhus, Denmark. Robophilosophy conferences are the world’s largest events for fully interdisciplinary social-robotics research, featuring contributions from humanities and social-science research in HRI, robotics, AI research, and cognitive science, as well as art events.

RP2024 explored the questions of socio-cultural transformation that can be expected to ensue from the new technological potential of social robotics. As is characteristic for the conferences in this series, RP2024 addressed not only questions of concrete practice, but also the deeper theoretical and existential issues that reach far beyond safety and privacy concerns into the conceptual and normative fabric of our societies and our individual self-comprehension.

The book is divided into 3 parts. Part 1 contains abstracts of the 8 plenary sessions; Part 2 contains 55 session papers divided into 8 sections; and Part 3 contains details of the 10 workshops which formed part of the conference.

The book showcases the way in which technical empirical, conceptual and phenomenological research can make a concrete contribution to the necessary collaborative effort, and will be of interest to all those working in the field.

Editors: Seibt, J., Fazekas, P., Quick, O.S.
Pages: 732
Volume 397 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-568-7

Fuzzy Systems and Data Mining X


Proceedings of FSDM 2024, Matsue, Japan, 5-8 November 2024

A fuzzy system is a system that uses fuzzy logic to associate variables and process information. Fuzzy systems are used in many applications, including machine control, air conditioning, and traffic control. Fuzzy systems also underlie almost every item of news that has any qualitative part, and numbers are translated into words in many daily activities, such as the weather forecast, or topics such as the economy and industry.

This book presents the proceedings of FSDM 2024, the 10th International Conference on Fuzzy Systems and Data Mining, held from 5 to 8 November 2024 in Matsue, Japan. With an emphasis on fuzzy theory, algorithm and system, fuzzy application, data mining and the interdisciplinary field of fuzzy logic and data mining, FSDM 2024 also included special sessions on hot topics in related research fields, including special sessions on applied mathematics and intelligent algorithms for modern industry (AMIAMI), the application of generative AI, and safeguarding AI-based automotive and automation products. A total of 237 submissions were received for the conference, and after undergoing a thorough review process, 71 papers were accepted for presentation and inclusion here, resulting in an acceptance rate of 30%. The papers are divided into 3 sections: fuzzy set theory, algorithm and system; data mining; and the interdisciplinary field of fuzzy logic and data mining.

Providing an overview of current research and development, the book will be of interest to all those using fuzzy systems and data mining as part of their work.

Editors: Tallón-Ballesteros, A.J.
Pages: 682
Volume 398 of Frontiers in Artificial Intelligence and Applications
ISBN online: 978-1-64368-569-4

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