ECAI 2023

26th European Conference on Artificial Intelligence, September 30 – October 4, 2023, Kraków, Poland – Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023)

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.

Editors: Gal, K., Nowé, A., Nalepa, G.J., Fairstein, R., Rădulescu, R.
Pages: 3326
Binding: softcover
Volume 372 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-436-9
ISBN online: 978-1-64368-437-6

Digitalization and Management Innovation

Proceedings of DMI 2022

The digital era has brought about important changes that continue to affect all our lives. Efficient management and storage of digital information has become crucial, as has the ability to access that information quickly and efficiently, and priorities are to allow for the saving of digital data in many different ways, and to avoid the loss of information in the event of a malfunction.

This book presents the 65 papers presented at DMI2022, the first in the new annual conference series Digitalization and Management Innovation (DMI), held as a hybrid event in Beijing, China, on 26 November 2022. A total of 190 submissions were received for the conference, and the papers presented here were selected after careful and conscientious review, bearing in mind the breadth and depth of the research topics falling within the scope of digital and management innovation and resulting in an acceptance rate of 34%. Topics covered include digital transformation, supply chains, business models, and block chain, enterprises, banking, and sustainability, as well as policy in artificial intelligence, the gig economy, the post-epidemic era, green supply, citizenship behavior, human resource management, human relationships, agriculture, and environmental matters.

Presenting original ideas and results of general significance and supported by clear reasoning, and compelling evidence and methods, the book will be of interest to all those whose work involves the management of digital data.

Editors: Tallón-Ballesteros, A.J., Santana-Morales, P.
Pages: 684
Binding: softcover
Volume 367 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-378-2
ISBN online: 978-1-64368-379-9

Design Studies and Intelligence Engineering

Proceedings of DSIE 2022

The technologies applied in design studies vary from basic theories to more application-based systems. Intelligence engineering also plays a significant role in design sciences such as computer-aided industrial design, human factor design, and greenhouse design, and intelligent engineering technologies such as computational technologies, sensing technologies, and video detection encompass both theory and application perspectives. Being multidisciplinary in nature, intelligence engineering promotes cooperation, exchange and discussion between organizations and researchers from diverse fields.

This book presents the proceedings of DSIE 2022, the International Symposium on Design Studies and Intelligence Engineering, held in Hangzhou, China, on 29 & 30 October 2022. This annual conference proves a platform for professionals and researchers from industry and academia to exchange and discuss recent advances in the field of design studies and intelligence engineering, inviting renowned experts from around the world to speak on their specialist topics, and allowing for in-depth discussion with presenters. The 189 submissions received were each carefully reviewed by 3 or 4 referees, and the 62 papers accepted for presentation and publication were selected based on their scores. Papers cover a very wide range of topics, from the design of a bachelor apartment, or a children’s backpack for healthy spine development, to interpretable neural symbol learning methods and design elements extraction from point-cloud datasets using deep enhancement learning.

Offering a varied overview of recent developments in design and intelligence engineering, this book will be of interest to all those working in the field.
Editors: Jain, L.C., Balas, V.E., Wu, Q., Shi, F.
Pages: 666
Binding: softcover
Volume 365 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-372-0
ISBN online: 978-1-64368-373-7

Information Modelling and Knowledge Bases XXXIV

The amount and complexity of information is continually growing, and information modeling and knowledge bases have become important contributors to technology and to academic and industrial research in the 21st century. They address the complexities of modeling in digital transformation and digital innovation, reaching beyond the traditional borders of information systems and academic computer-science research.

This book presents the proceedings of EJC 2022, the 32nd International conference on Information Modeling and Knowledge Bases, held as a hybrid event due to restrictions related to the Corona virus pandemic in Hamburg, Germany, from 30 May to 3 June 2022. The aim of the conference is to bring together experts from different areas of computer science and other disciplines with a common interest in understanding and solving the problems of information modeling and knowledge bases and applying the results of research to practice. The conference has always been open to new topics related to its main themes, and the content emphasis of the conferences have changed through the years according to developments in the research field, so philosophy and logic, cognitive science, knowledge management, linguistics, and management science, as well as machine learning and AI, are also relevant areas. This book presents 19 reviewed and selected papers covering a wide range of topics, upgraded as a result of comments and discussions during the conference.

Providing a current overview of recent developments, the book will be of interest to all those using information modeling and knowledge bases as part of their work.
Editors: Tropmann-Frick, M., Jaakkola, H., Thalheim, B., Kiyoki, Y., Yoshida, N.
Pages: 290
Binding: softcover
Volume 364 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-370-6
ISBN online: 978-1-64368-371-3

Social Robots in Social Institutions

Proceedings of Robophilosophy 2022

Social institutions emerge from social practices which coordinate activities by the explicit statement of rules, goals, and values. When artificial social actors are introduced into the physical and symbolic space of institutions, will this affect or transform institutional structures and practices, and how can social robotics as an interdisciplinary endeavor contribute to the ability of our institutions to perform their functions in society?

This book presents the Proceedings of Robophilosophy 2022, the 5th event in the biennial Robophilosophy conference series, held in Helsinki, Finland, from 16 to 19 August 2022. The theme of this edition of the conference was Social Robots in Social Institutions, and it featured international multidisciplinary research from the humanities, social sciences, Human-Robot Interaction, and social robotics. The 63 papers, 41 workshop papers and 5 posters included in this book are divided into 4 sections: plenaries, sessions, workshops and posters, with the 41 papers in the ‘Sessions’ section grouped into 13 subdivisions including elderly care, healthcare, law, education and art, as well as ethics and religion. These papers explore the anticipated conceptual and practical changes which will come about in the course of introducing social robotics into public and private institutions, such as public services, legal systems, social and healthcare services, or educational institutions.

The research contributions collected here offer cutting edge explorations of the societal significance of social robots for the future of social institutions – they will be of interest to both researchers in Robophilosophy, Human-Robot Interactions, and robotics, as well as private companies and policy makers aiming to place artificial social agents in social institutions.
Editors: Hakli, R., Mäkelä, P., Seibt, J.
Pages: 798
Binding: softcover
Volume 366 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-374-4
ISBN online: 978-1-64368-375-1

Machine Learning and Artificial Intelligence

Proceedings of MLIS 2022

Machine learning (ML) and artificial intelligence (AI) applications are now so pervasive that they have become indispensable facilitators which improve the quality of all our daily lives.

This book presents the proceeding of MLIS 2022, the 4th International Conference on Machine Learning and Intelligent Systems, held as a virtual event due to the continued uncertainty caused by the Covid-19 pandemic and hosted in Seoul, South Korea from 8 to 11 November 2022. The aim of the annual MLIS conference is to provide a platform for the exchange of the most recent scientific and technological advances in the field of machine learning and intelligent systems, and to strengthen links in the scientific community in related research areas. Scientific topics covered at MLIS 2022 included data mining, image processing, neural networks, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. The book contains the 20 papers selected for acceptance after a rigorous peer review process from the more than 90 full papers submitted. Selection criteria were based on originality, scientific/practical significance, compelling logical reasoning and language, and the 20 papers included here all provide either innovative and original ideas or results of general significance in the field of ML and AI.

Providing an overview of the latest research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.
Editor: Kim, J.-L
Pages: 170
Binding: softcover
Volume 360 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-356-0
ISBN online: 978-1-64368-357-7

Proceedings of CECNet 2022

The 12th International Conference on Electronics, Communications and Networks (CECNet 2022), 4-7 November 2022

Electronics, communication and networks coexist, and it is not possible to conceive of our current society without them. Within the next decade we will probably see the consolidation of 6G-based technology, accompanied by many compatible devices, and fiber-optic is already an advanced technology with many applications.

This book presents the proceedings of CECNet 2022, the 12th International Conference on Electronics, Communications and Networks, held as a virtual event with no face-to-face participation in Xiamen, China, from 4 to 7 November 2022. CECNet is held annually, and covers many interrelated groups of topics such as electronics technology, communication engineering and technology, wireless communications engineering and technology and computer engineering and technology. This year the conference committee received 313 submissions. All papers were carefully reviewed by program committee members, taking into consideration the breadth and depth of research topics falling within the scope of the conference, and after further discussion, 79 papers were selected for presentation at the conference and for publication in this book. This represents an acceptance rate of about 25%. 

The book offers an overview of the latest research and developments in these rapidly evolving fields, and will be of interest to all those working with electronics, communication and networks.
Editor: Tallón-Ballesteros, A.J.
Pages: 694
Binding: softcover
Volume 363 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-368-3
ISBN online: 978-1-64368-369-0

Exploiting Environment Configurability in Reinforcement Learning

In recent decades, Reinforcement Learning (RL) has emerged as an effective approach to address complex control tasks. In a Markov Decision Process (MDP), the framework typically used, the environment is assumed to be a fixed entity that cannot be altered externally. There are, however, several real-world scenarios in which the environment can be modified to a limited extent. 

This book, Exploiting Environment Configurability in Reinforcement Learning, aims to formalize and study diverse aspects of environment configuration. In a traditional MDP, the agent perceives the state of the environment and performs actions. As a consequence, the environment transitions to a new state and generates a reward signal. The goal of the agent consists of learning a policy, i.e., a prescription of actions that maximize the long-term reward. Although environment configuration arises quite often in real applications, the topic is very little explored in the literature. The contributions in the book are theoretical, algorithmic, and experimental and can be broadly subdivided into three parts. The first part introduces the novel formalism of Configurable Markov Decision Processes (Conf-MDPs) to model the configuration opportunities offered by the environment. The second part of the book focuses on the cooperative Conf-MDP setting and investigates the problem of finding an agent policy and an environment configuration that jointly optimize the long-term reward. The third part addresses two specific applications of the Conf-MDP framework: policy space identification and control frequency adaptation. 

The book will be of interest to all those using RL as part of their work.

Author: Metelli, A.M.
Pages: 376
Binding: softcover
Volume 361 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-362-1
ISBN online: 978-1-64368-363-8

Legal Knowledge and Information Systems

JURIX 2022: The Thirty-fifth Annual Conference, Saarbrücken, Germany, 14-16 December 2022

In recent years, interest within the research community and the legal industry regarding technological advances in legal knowledge representation and processing has been growing. This relates to areas such as computational models of legal reasoning, cybersecurity, privacy, trust and blockchain methods, among other things.

This book presents the proceedings of JURIX 2022, the 35th International Conference on Legal Knowledge and Information Systems, held from 14 –16 December in Saarbrücken, Germany, under the auspices of the Dutch Foundation for Legal Knowledge Based Systems and hosted by Saarland University. The annual JURIX conference has become an international forum for academics and professionals to exchange knowledge and experiences at the intersection of law and artificial intelligence (AI). For this edition, 62 submissions were received from 163 authors in 24 countries. Following a rigorous review process, carried out by a programme committee of 72 experts recognised in the field, 14 submissions were selected for publication as long papers, 22 as short papers and 5 as demo papers, making a total of 41 papers altogether and representing a 22.5% acceptance rate for long papers (66.1% overall). The broad array of topics covered includes argumentation and legal reasoning, legal ontologies and the semantic web, machine and deep learning and natural language processing for legal knowledge extraction, as well as argument mining, translation of legal texts, defeasible logic, legal compliance, explainable AI, alternative dispute resolution, legal drafting and smart contracts.

Providing an overview of recent advances, the book will be of interest to all those working at the interface between the law and AI.

Editors: Francesconi, E., Borges, G., Sorge, C.
Pages: 322
Binding: softcover
Volume 362 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-364-5
ISBN online: 978-1-64368-365-2

Deep Learning with Relational Logic Representations

Deep learning has been used with great success in a number of diverse applications, ranging from image processing to game playing, and the fast progress of this learning paradigm has even been seen as paving the way towards general artificial intelligence. However, the current deep learning models are still principally limited in many ways.

This book, ‘Deep Learning with Relational Logic Representations’, addresses the limited expressiveness of the common tensor-based learning representation used in standard deep learning, by generalizing it to relational representations based in mathematical logic. This is the natural formalism for the relational data omnipresent in the interlinked structures of the Internet and relational databases, as well as for the background knowledge often present in the form of relational rules and constraints. These are impossible to properly exploit with standard neural networks, but the book introduces a new declarative deep relational learning framework called Lifted Relational Neural Networks, which generalizes the standard deep learning models into the relational setting by means of a ‘lifting’ paradigm, known from Statistical Relational Learning. The author explains how this approach allows for effective end-to-end deep learning with relational data and knowledge, introduces several enhancements and optimizations to the framework, and demonstrates its expressiveness with various novel deep relational learning concepts, including efficient generalizations of popular contemporary models, such as Graph Neural Networks.

Demonstrating the framework across various learning scenarios and benchmarks, including computational efficiency, the book will be of interest to all those interested in the theory and practice of advancing representations of modern deep learning architectures.

Author: Šír, G.
Pages: 238
Binding: softcover
Volume 357 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-342-3
ISBN online: 978-1-64368-343-0


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