Fuzzy Systems and Data Mining VIII


Proceedings of FSDM 2022

Fuzzy logic is vital to applications in the electrical, industrial, chemical and engineering realms, as well as in areas of management and environmental issues. Data mining is indispensible in dealing with big data, massive data, and scalable, parallel and distributed algorithms.

This book presents papers from FSDM 2022, the 8th International Conference on Fuzzy Systems and Data Mining. The conference, originally scheduled to take place in Xiamen, China, was held fully online from 4 to 7 November 2022, due to ongoing restrictions connected with the COVID-19 pandemic. This year, FSDM received 196 submissions, of which 47 papers were ultimately selected for presentation and publication after a thorough review process, taking into account novelty, and the breadth and depth of research themes falling under the scope of FSDM. This resulted in an acceptance rate of 23.97%. Topics covered include fuzzy theory, algorithms and systems, fuzzy applications, data mining and the interdisciplinary field of fuzzy logic and data mining.

Offering an overview of current research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Editors: Tallón-Ballesteros, A.J.
Pages: 438
Binding: softcover
Volume 358 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-346-1
ISBN online: 978-1-64368-347-8

Advanced Tools and Methods for Treewidth-Based Problem Solving

This book, Advanced Tools and Methods for Treewidth-Based Problem Solving, contains selected results from the author’s PhD studies, which were carried out from 2015 to 2021. For his PhD thesis, Markus Hecher received the EurAI Dissertation Award 2021 and the GI Dissertation Award 2021, amongst others.

The aim of the book is to present a new toolkit for using the structural parameter of treewidth to solve problems in knowledge representation and reasoning (KR) and artificial intelligence (AI), thereby establishing both theoretical upper and lower bounds, as well as methods to deal with treewidth efficiently in practice. The key foundations outlined in the book provide runtime lower bounds – under reasonable assumptions in computational complexity – for evaluating quantified Boolean formulas and logic programs which match the known upper bounds already published in 2004 and 2009.

The general nature of the developed tools and techniques means that a wide applicability beyond the selected problems and formalisms tackled in the book is anticipated, and it is hoped that the book will serve as a starting point for future theoretical and practical investigations, which will no doubt establish further results and gain deeper insights.

Editors: Hecher, M.
Pages: 250
Binding: softcover
Volume 359 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-344-7
ISBN online: 978-1-64368-345-4

Augmenting Human Intellect


Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence

Hybrid human-artificial intelligence is a new research area concerned with all aspects of AI systems that assist humans, and vice versa. The emphasis is on the need for adaptive, collaborative, responsible, interactive and human-centered artificial intelligence systems that can leverage human strengths and compensate for human weaknesses while taking into account social, ethical and legal considerations. The challenge is to develop robust, trustworthy AI systems that can ‘understand’ humans, adapt to complex real-world environments and interact appropriately in a variety of social settings.

This book presents the proceedings of the 1st International Conference on Hybrid Human-Artificial Intelligence (HHAI2022), held in Amsterdam, The Netherlands, from 13 -17June 2022. HHAI2022 was the first international conference focusing on the study of AI systems that amplify rather than replace human intelligence by cooperating synergistically, proactively, responsibly and purposefully with humans. Scholars from the fields of AI, human computer interaction, cognitive and social sciences, computer science, philosophy, and others were invited to submit their best original work on hybrid human-artificial intelligence. The book contains 24 main-track papers, 17 poster and demo papers, and 1 Hackathon paper, selected from a total of 96 submissions, and topics covered include human-AI interaction and collaboration, co-learning and co-creation; learning, reasoning and planning with humans and machines in the loop; integration of learning and reasoning; law and policy challenges around human-centered AI systems; and societal awareness of AI.

The book provides an up-to-date overview of this novel and timely field of study, and will be of interest to all those working with aspects of artificial intelligence, in whatever field.

Editors: Schlobach, S., Pérez-Ortiz, M., Tielman, M.
Pages: 346
Binding: softcover
Volume 354 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-308-9
ISBN online: 978-1-64368-309-6

Artificial Intelligence Research and Development


Proceedings of the 24th International Conference of the Catalan Association for Artificial Intelligence

Artificial intelligence has become an integral part of all our lives. Development is rapid in this exciting and far-reaching field, and keeping up to date with the latest research and innovation is crucial to all those working with the technology.

This book presents the proceedings of the 24th edition of CCIA, the International Conference of the Catalan Association for Artificial Intelligence, held in Sitges, Spain, from 19 – 21 October 2022. This annual event serves as a meeting point not only for researchers in AI from the Catalan speaking territories (southern France, Catalonia, Valencia, the Balearic Islands and Alghero in Italy) but for researchers from around the world. The programme committee received 59 submissions, from which the 26 long papers and 23 short papers selected for presentation at the conference by the 62 experts who make up the committee are included here. The book is divided into the following sections: combinatorial problem solving and logics for artificial intelligence; sentiment analysis and tekst analysis; data science, recommender systems and decision support systems; machine learning; computer vision; and explainability and argumentation. This book also includes an abstract of the invited talk given by Prof. Fosca Giannotti.

Providing a comprehensive overview of research and development, this book will be of interest to all those working in the field of Artificial Intelligence.

Editors: Cortés, A., Grimaldo, F., Flaminio, T.
Pages: 388
Binding: softcover
Volume 356 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-326-3
ISBN online: 978-1-64368-327-0

Modern Management based on Big Data III


Proceedings of MMBD 2022

Data is the basic ingredient of all Big Data applications, and Big Data technologies are constantly deploying new strategies to maximise efficiency and reduce the time taken to process information.

This book presents the proceedings of MMBD2022, the third edition of the conference series Modern Management based on Big Data (MMBD). The conference was originally scheduled to take place from 15 to 18 August 2022 in Seoul, South Korea, but was changed to a virtual event on the same dates. Some 200 submissions were received for presentation at the conference, 52 of which were ultimately accepted after exhaustive review by members of the programme committee and peer-reviewers, who took into account the breadth and depth of the research topics and the scope of MMBD. Topics covered include data analytics, modelling, technologies and visualization, architectures for parallel processing systems, data mining tools and techniques, machine learning algorithms, and big data for engineering applications. There are also papers covering modern management, including topics such as strategy, decision making, manufacturing and logistics-based systems, engineering economy, information systems and law-based information treatment, and papers from a special session covering big data in manufacturing, retail, healthcare, accounting, banking, education, global trading, and e-commerce. Big data analysis and emerging applications were popular topics.

The book includes many innovative and original ideas, as well as results of general significance, all supported by clear and rigorous reasoning and compelling evidence and methods, and will be of interest to all those working with Big Data.

Editors: Tallón-Ballesteros, A.J
Pages: 496
Binding: softcover
Volume 352 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-300-3
ISBN online: 978-1-64368-301-0

Computational Models of Argument


Proceedings of COMMA 2022

This volume presents papers from the Third Conference on Computational Models of Argument, held in September 2010 in Desanzano del Garda, Italy.

Argumentation has been the subject of research in a number of different fields where a solution is sought for the many problems encountered in the knowledge representation and reasoning area of artificial intelligence. The goal is the development of applications using strategies akin to the commonsense approach applied by humans. In recent years such practical applications of basic research results have been the subject of increasing attention, especially within the autonomous agents and multiagent systems community. To answer the need for a forum where advances in the field could be discussed in a specialised manner by members of the argumentation community, the first conference in this series was held in 2006 at the University of Liverpool. The success of both the first and the subsequent second conference, held in Toulouse in 2008, has established this conference as a biennial event.

The call for papers for the third conference resulted in the submission of 67 papers, of which the 35 full papers and five short papers selected are presented here, along with two invited papers from prof. Gerhard Brewka and prof. Douglas Walton. Subjects covered range from formal models of argumentation and the relevant theoretical questions, through algorithms and computational complexity issues, to the use of argumentation in several application domains.

Overall this volume provides an up to date view of this important research field and will be of interest to all those involved in the use and development of artificial intelligence systems.

Editors: Toni, F., Polberg, S., Booth, R., Caminada, M., Kido, H.
Pages: 398
Binding: softcover
Volume 353 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-306-5
ISBN online: 978-1-64368-307-2

PAIS 2022


11th Conference on Prestigious Applications of Artificial Intelligence, 25 July 2022, Vienna, Austria (co-located with IJCAI-ECAI 2022)

Artificial Intelligence (AI) is a central topic in contemporary computer science; one which has enabled many groundbreaking developments that have significantly influenced our society. Not only has it proved to be of fundamental importance in areas such as medicine, biology, economics, philosophy, linguistics, psychology and engineering, but it has also had a significant impact in a number of fields, including e-commerce, tourism, e-government, national security, manufacturing and other economic sectors.

This book contains the proceedings of PAIS 2022, the 11th Conference on Prestigious Applications of Artificial Intelligence, held in Vienna, Austria, on 25 July 2022 as a satellite event of IJCAI-ECAI 2022. The PAIS conference invites papers describing innovative applications of AI techniques to real-world systems and problems, and aims to provide a forum for academic and industrial researchers and practitioners to share their experience and insight on the applicability, development and deployment of intelligent systems. A total of 18 full-paper submissions and 4 extended-abstract submissions were received for the 2022 conference, of which 10 full papers and 3 extended abstracts were accepted after rigorous peer review. The topics covered range from autonomous navigation, air traffic control and satellite management to the optimization of industrial processes and human-in-the-loop applications.

The book will be of interest to all those whose work involves the innovative application of AI techniques to real-world situations.

Editors: Passerini, A., Schiex, T.
Pages: 170
Binding: softcover
Volume 351 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-294-5
ISBN online: 978-1-64368-295-2

Hybrid Offline/Online Methods for Optimization Under Uncertainty


Balancing the solution-quality/time trade-off and optimizing problems which feature offline and online phases can deliver significant improvements in efficiency and budget control. Offline/online integration yields benefits by achieving high quality solutions while reducing online computation time.

This book considers multi-stage optimization problems under uncertainty and proposes various methods that have broad applicability. Due to the complexity of the task, the most popular approaches depend on the temporal granularity of the decisions to be made and are, in general, sampling-based methods and heuristics. Long-term strategic decisions that may have a major impact are typically solved using these more accurate, but expensive, sampling-based approaches. Short-term operational decisions often need to be made over multiple steps within a short time frame and are commonly addressed via polynomial-time heuristics, with the more advanced sampling-based methods only being applicable if their computational cost can be carefully managed. Despite being strongly interconnected, these 2 phases are typically solved in isolation.

In the first part of the book, general methods based on a tighter integration between the two phases are proposed and their applicability explored, and these may lead to significant improvements. The second part of the book focuses on how to manage the cost/quality trade-off of online stochastic anticipatory algorithms, taking advantage of some offline information.

All the methods proposed here provide multiple options to balance the quality/time trade-off in optimization problems that involve offline and online phases, and are suitable for a variety of practical application scenarios.

Author:De Filippo, A.
Pages: 124
Binding: softcover
Volume 349 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-262-4
ISBN online: 978-1-64368-263-1

Learning and Reasoning in Hybrid Structured Spaces


Artificial intelligence often has to deal with uncertain scenarios, such as a partially observed environment or noisy observations. Traditional probabilistic models, while being very principled approaches in these contexts, are incapable of dealing with both algebraic and logical constraints. Existing hybrid continuous/discrete models are typically limited in expressivity, or do not offer any guarantee on the approximation errors.

This book, Learning and Reasoning in Hybrid Structured Spaces, discusses a recent and general formalism called Weighted Model Integration (WMI), which enables probabilistic modeling and inference in hybrid structured domains. WMI-based inference algorithms differ with respect to most alternatives in that probabilities are computed inside a structured support involving both logical and algebraic relationships between variables. While the research in this area is at an early stage, we are witnessing an increasing interest in the study and development of scalable inference procedures and effective learning algorithms in this setting.

This book details some of the most impactful contributions in context of WMI-based inference in the last 5 years. Moreover, by providing a gentle introduction to the main concepts related to WMI, the book can be useful for both theoretical researchers and practitioners alike.

Author: Morettin, P.
Pages: 110
Binding: softcover
Volume 350 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-266-2
ISBN online: 978-1-64368-267-9

Abstraction in Ontology-based Data Management


Effectively documenting data services is a crucial issue in any organization, not only for governing data but also for interoperation purposes. Indeed, in order to fully realize the promises and benefits of a data-driven society, data-driven approaches need to be resilient, transparent, and fully accountable.

This book, Abstraction in Ontology-based Data Management, proposes a new approach to automatically associating formal semantic description to data services, thus bringing them into compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) guiding principles. The approach is founded on the Ontology-based Data Management (OBDM) paradigm, in which a domain ontology is used to provide a high-level semantic layer mapped to the source schema of an organization containing data, thus abstracting from the technical details of the data layer implementation. A formal framework for a novel reasoning task in OBDM, called Abstraction, is introduced in which a data service is assumed to be expressed as a query over the source schema, and the aim is to derive a query over the ontology that semantically describes the given data service best with respect to the underlying OBDM specification. In a general scenario that uses the most popular languages in the OBDM literature, an in-depth complexity analysis of two computational problems associated with the framework is carried out. Also investigated is the problem of expressing abstractions in a non-monotonic query language as well as the impact of adding inequalities. Regarding the latter, the problem of answering queries with inequalities over lightweight ontologies is first studied. Lastly, the author illustrates how the achieved results contribute to new results in the Semantic Web context and in the Relational Database theory.

The book will be of interest to all those engaged in Artificial Intelligence and Data Management.

Author: Cima, G.
Pages: 268
Binding: softcover
Volume 348 of Frontiers in Artificial Intelligence and Applications
ISBN print: 978-1-64368-258-7
ISBN online: 978-1-64368-259-4

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