Approved Special Sessions
- SS01: In honor of Michio Sugeno
- SS02: Theoretical and applied aspects of Imprecise Probabilities
- SS03: New directions in data aggregation
- SS04: Information fusion techniques based on aggregation functions, preaggregation functions and their generalizations
- SS05: Representing and Managing Uncertainty: different scenarios, different tools
- SS06: Fuzzy Implication Functions
- SS07: Soft Methods in Statistical Inference and Data Analysis
- SS08: Evaluative linguistic expressions and generalized quantifiers: theory and applications
- SS09: Dynamic decision models under uncertainty and imprecision
- SS10: Flexible advanced mining methods for data, text and social networks
- SS11: Logic-based Decision Making
- SS12: Special session on soft computing, uncertainty and imprecision in image processing
- SS13: Fuzzy Modelling and Control
- SS14: EUSFLAT Working Group on Aggregation Operators
- SS15: EUSFLAT Working Group on Fuzzy Logic-Based Decision Modeling in Economics and Social Sciences
- SS16: EUSFLAT Working Group on Genetic Fuzzy Systems
- SS17: EUSFLAT Working Group on Intuitionistic Fuzzy Sets: Theory, Applications and Related Topics
- SS18: EUSFLAT Working Group on Learning and Data Mining
- SS19: EUSFLAT Working Group on Mathematical Fuzzy Logic
- SS20: EUSFLAT Working Group on Philosophical Foundations
- SS21: EUSFLAT Working Group on Soft Computing in Database Management and Information Retrieval
SS01: In honor of Michio Sugeno
This session is organised in homage to Michio Sugeno and aims at bringing together researchers who contributed to the rich works he initiated. It will accept works related to his life and his scientific contributions, among which the Sugeno integral plays a major role: in his phd in 1974 Michio Sugeno provided a qualitative counterpart to measure theory, through the fuzzy measure theory, and he defined the Sugeno integral. This integral, commonly used in qualitative evaluation, initiates representations and computations for qualitative data among many others.
- Agnès Rico, Université de Lyon 1, France
SS02: Theoretical and applied aspects of Imprecise Probabilities
Description This session is dedicated to Imprecise Probability Theory. This theory encompasses all the mathematical models that provide a flexible alternative to Probability Theory when the available information is scarce, vague or incomplete. It includes lower previsions, n-monotone capacities, belief functions, possibility measures, or non-additive measures, among others.
This special session aims to include papers related to Imprecise Probabilities that either present a significant advance in the foundations or demonstrate potential applications in real-world problems. Additionally, papers where the connection between imprecise probability theories and other fields such as fuzzy sets or game theory is emphasised are also welcome.
- Enrique Miranda, University of Oviedo, Spain
- Ignacio Montes, University of Oviedo, Spain
SS03: New directions in data aggregation
Since the early days of fuzzy set theory, aggregation functions have been an invaluable ally for researchers in the field. It is not surprising then that aggregation theory has quickly grown to become a core subfield of fuzzy set theory. Typically, within fuzzy set theory, aggregation functions have been used for aggregating degrees of truth/membership, which usually are values within the unit interval. For this very reason, the impressive body of mathematical knowledge that has been developed around the notion of aggregation function has been mostly restricted to functions operating on the unit interval or, more generally, on a bounded interval. However, aggregation processes have been used for ages outside aggregation theory for aggregating data of a very different nature: (multivariate) real-valued data (statistics), ranking data (social choice theory), string data (computer science), compositional data (geochemistry), directional data (biology), imagery data (computer vision), etc.
This special session follows a long-standing tradition at past IPMU conferences providing a forum for researchers dealing with aggregation on less popular structures. All contributions dealing with the aggregation on structures different from a real-valued interval are welcome. Theoretical, applied as well as algorithmical contributions are welcome.
- Bernard De Baets, Ghent University, Belgium
- Raúl Pérez-Fernández, University of Oviedo, Spain
SS04: Information fusion techniques based on aggregation functions, preaggregation functions and their generalizations
The search of new information fusion techniques under uncertainty is currently a hot topic in almost every research field, from image processing, classification, data stream clustering, brain computer interfaces, decision making to deep learning and adaptive neuro fuzzy inference systems. This interest has led to new analysis of the notion of aggregation function and the introduction of new concepts that go beyond usual aggregation functions, either by considering more general definitions (e.g., considering weaker forms of monotonicity), or by extending them to other frameworks different from that of the unit interval (e.g., intervals, lattices). The aim of this section is to promote the discussion of the up-to-date theoretical research in the topic, as well as their applications, in total connection with the interests of IPMU 2024, related to the theoretical and applied subjects covered by conference.
- Humberto Bustince, Universidad Publica de Navarra, Spain
- Graçaliz Pereira Dimuro, Universidade Federal do Rio Grande, Brazil
- Javier Fernández, Universidad Publica de Navarra, Spain
- Tiago da Cruz Asmus, Universidade Federal do Rio Grande do Norte, Brazil
- Benjamin Bedregal, Universidade Federal do Rio Grande do Norte, Brazil
SS05: Representing and Managing Uncertainty: different scenarios, different tools
The notion of uncertainty has been extensively analysed in the last decades by philosophers, logicians and computer scientists. Here we are interested in the uncertainty originated by different characteristics and flaws in information: incompleteness, imprecision, graduality, granularity, contradiction between agents, etc. For each of these aspects one (or more) specific tool has been introduced in literature: fuzzy sets, rough sets, formal concept analysis, possibility theory, Dempster-Shafer theory, interval analysis, compound objects comparators, etc. Further, when more than one form of uncertainty is present at the same time, it seems natural to fuse such tools, as in the fuzzy rough set case. The special session is devoted to collect all contributions that deal with scenarios leading to a form of uncertainty and tools to represent and manage it. In particular, all critical discussions, comparisons among two or more forms of uncertainty and/or comparisons and fusion of two or more tools are welcome.
The not exhaustive list of topics includes:
- fuzzy rough sets
- interval-valued fuzzy sets
- formal concept analysis
- mathematical morphology
- fuzzy relation equations
- possibility theory
- Dempster-Shafer theory
- near sets
- interval analysis
- non-classical logics (many valued, paraconsistent, epistemic, etc.)
- similarity-based reasoning
- networks of comparators
- Davide Ciucci, University of Milano-Bicocca, Italy
- Chris Cornelis, Ghent University, Belgium
- Jesus Medina, Universidad de Cádiz, Spain
- Dominik Slezak, University of Warsaw, Poland
SS06: Fuzzy Implication Functions
From more than a decade now, fuzzy implication functions have become one of the main research lines of the fuzzy logic community. These logical connectives are the generalization of the classical two-valued implication to the infinite-valued setting. In addition to modelling fuzzy conditionals, they are also used to perform backward and forward inferences in different fuzzy rule based systems. Moreover, they have proved to be useful not only in fuzzy control and approximate reasoning, but also in many other fields such as Multi-Valued Logic, Image Processing, Data Mining, Computing with Words and Rough Sets, among others.
Due to this great variety of applications, fuzzy implication functions have attracted the efforts of many researchers from the points of view of both theory and applications. Indeed, the theoretical perspective focuses on problems whose solutions provide important insights from the point of view of their applications. Therefore, this special session seeks to bring together researchers interested in recent advances in the theory and the applications of fuzzy implication functions, concerning, among others, characterizations, representations, generalizations and their relationships with fuzzy negations, triangular norms, uninorms and other fuzzy logic connectives.
- Michal Baczynski, University of Silesia in Katowice, Poland
- Balasubramaniam Jayaram, Indian Institute of Technology Hyderabad, India
- Sebastia Massanet, University of the Balearic Islands, Spain
SS07: Soft Methods in Statistical Inference and Data Analysis
A growing diversity of data types and the increasing complexity of problems considered in science and practical applications reveal the need for more flexible tools for uncertainty modeling. New challenges faced by data analysts require new inferential techniques and soft computing methods that adapt more easily to the actual nature of data, integrate different aspects of uncertainty (including randomness, imprecision, ambiguity, etc.), and could be combined with machine learning. This Special Session aims to bring together theoreticians and practitioners in statistical reasoning and data analysis to discuss emerging challenges and exchange ideas to develop new inferential methods that will improve understanding and solve specific problems.
Topics of interest include but are not limited to
- Analysis of censored or missing data
- Analysis of fuzzy data
- Bayesian methods
- Clustering and classification
- Data mining
- Fuzzy random variables
- Fuzzy regression methods
- Granular computing
- Interval data
- Machine learning
- Possibility theory
- Random sets
- Robust statistics
- Semi-supervised learning
- Streaming data
- Soft computing
- Statistical software for imprecise data
- Time series analysis and forecasting
- Przemyslaw Grzegorzewski, Warsaw University of Technology, Poland
- Katarzyna Kaczmarek-Majer, Polish Academy of Sciences, Poland
- Jin Hee Yoon, Sejong University, South Korea
SS08: Evaluative linguistic expressions and generalized quantifiers: theory and applications
Fuzzy sets have been proven successful in linguistically summarizing numerical data in various contexts such as psychology, economics, political sciences, medicine, engineering, etc. The primary advantage of evaluative linguistic expressions is their human consistency. Evaluative linguistic expressions are terms in natural language such as small, medium, big, about twenty-five, very short, more or less deep, not very tall, quite roughly strong, and many others. Such expressions are present in everyday life when making decisions, learning new skills, and in many other activities.
An interesting group of natural language expressions are generalized quantifiers, for example, most, a lot of, many, a few, a great deal of, a large part of, etc. Generalized quantifiers have been proven successful in linguistically summarising numerical data and extracting knowledge in the form of fuzzy association rules and linguistic summaries. Special Session aims to bring together theorists and practitioners in evaulative lingusitic expression, generalized and fuzzy quantifiers and linguistic summaries to discuss emerging challenges related to handling various sources of uncertainty and exchange ideas to develop new methods that will improve understanding of large datase
The aim of this special section is to provide a platform for discussion of new directions concerning evaluative linguistic expressions, generalized and fuzzy quantifiers, and related areas. It is focused on (but not limited to) the following topics:
- Generalized quantifiers
- Logical structures of opposition
- Logical syllogisms and their applications
- Linguistic and logical theory of evaluative expressions
- Linguistic summarization
- Fuzzy association rules
- Human-centered data representation using natural language
- Extended fuzzy concept analysis
- Fuzzy linguistic
- Vilém Novák, University of Ostrava, Czech Republic
- Petra Murinová, University of Ostrava, Czech Republic
- Katarzyna Kaczmarek-Majer, Polish Academy of Sciences, Poland
- Aleksandra Rutkowska, Poznan University of Economics and Business, Poland
SS09: Dynamic decision models under uncertainty and imprecision
Decision making is one of the most complex activities characterizing decision makers in the most diverse application domains, such as economics, social sciences and engineering. The complexity of phenomena requires to make decisions under partial knowledge, taking into account “imprecision” and “vagueness” that lead to ambiguous beliefs. Usually, these two aspects are studied separately, but the increasing availability of huge amounts of heterogeneous and imperfect data requires they are handled together. The theoretical framework relies on decision theory, game theory, non-additive measures and integrals and fuzzy set theory, for which the notion of conditioning is crucial to address information updating and achieve dynamic decision models.
Topics of interest of the special session include, but are not limited to:
- Decision making under uncertainty;
- Games under ambiguous information;
- Dynamic non-linear functionals and applications;
- Portfolio selection under ambiguity;
- Uncertainty and risk models under imprecise information.
- Davide Petturiti, University of Perugia, Italy
- Barbara Vantaggi, Sapienza University of Rome, Italy
SS10: Flexible advanced mining methods for data, text and social networks
The continual evolution and proliferation of information and communication technologies have precipitated the daily generation of extensive data. The inherent vagueness and intricacies in real-world data offer challenges and opportunities for researchers and companies.
Researchers and companies study and create algorithms and tools tailored to process and analyse the intricate nature of real-world data. These endeavours are geared towards enhancing downstream tasks in data, text, and social network mining, such as clustering, sentiment analysis, topic modelling,document classification, text summarisation, speech recognition, community detection, influence analysis, anomaly detection and more.
In the contemporary world, data, text, and social network mining solutions have been seamlessly incorporated into the fabric of nearly every domain. They transcend boundaries, finding applications in realms as diverse as politics, sports, healthcare, and beyond. The inherent imprecision of real-world data adds additional complexity, urging researchers and developers to navigate the intricacies of real-data nuances, ensuring that these solutions are robust and attuned to the subtleties of real-world data across various domains.
Topics of interest include, but are not limited to, the following topics:
- Flexible data, text, and web mining
- Data text and web mining approaches under uncertainty.
- Stream data mining
- Temporal data series
- Big data mining
- Imprecision, uncertainty, and vagueness in data mining
- Data pre- and post-processing in data mining
- Parallel and distributed data mining algorithms
- Information summarisation and visualisation
- Human-machine interaction for data access
- Semantic models to represent input data and extracted knowledge in a data mining process
- Applications of data mining techniques: health, tourism, biological process, customer profiles, anomaly detection, emergency management, situation recognition, etc.
- Information retrieval, search and question-answering
- Interpretability and analysis of models in data mining
- Community detection, influence analysis and anomaly detection
- Carlos J. Fernández-Basso, University of Granada, Spain
- Karel Gutiérrez-Batista, University of Granada, Spain
- José Ángel Diaz-Garcia, University of Granada, Spain
SS11: Logic-based Decision Making
The goal of proposed special session is to explore the latest theoretical advancements and real-world applications of logic-based decision-making approaches. As decision-making processes become increasingly complex, incorporating logic-based approaches becomes crucial for addressing real-world challenges. This special session will address both the theoretical developments and the applicability of logic-based paradigms in diverse decision-making scenarios. We are particularly interested in new developments of continuum-valued, andness-directed, importance weighted, and annihilators-selectable logic aggregators, and their use in solving evaluation, explainability, and decision confidence problems.
The special interest of the session will be focused on two strictly logic-based methodologies: Logic Aggregation (LA) based on Interpolative Boolean Algebra (IBA) and Logic Scoring of Preference (LSP) based on Graded Logic (GL).
Topics of interest include, but are not limited to:
- Logic Scoring of Preference (LSP) decision method;
- Logic aggregation based on Graded Logic (GL);
- Logic Aggregation (LA) based on Interpolative Boolean Algebra (IBA);
- Fuzzy logic and interval-valued fuzzy logic approaches to decision making;
- Real-valued logic-based operators (e.g., uninorms, hyperconjugation) in decision making context;
- Andness-characterized aggregators and andness-directedness;
- Importance weighting and human-centric logic aggregation;
- Logic aggregator modeling experiments with human subjects.
These topics have applications in various areas, including, Business and Finance, Medical decision making, Ecology, Computer science, Quality control, Bioinformatics, etc.
This special session will offer a forum for researchers and practitioners to exchange insights and share advancements regarding the decision-making problems faced in today’s complex environments. By focusing on logic-based approaches, participants will gain a deeper understanding of how these methodologies can contribute to the development of effective, transparent, and ethically sound decision support systems.
- Jozo Dujmović, San Francisco State University, USA
- Pavle Milošević, University of Belgrade, Serbia
- Ivana Dragović, University of Belgrade, Serbia
- Ana Poledica, University of Belgrade, Serbia
SS12: Special session on soft computing, uncertainty and imprecision in image processing
This session aims at gathering researchers interested and involved in uncertainty issues in processing and analysis of images, in various applications. Uncertainty (in a broad sense) can pertain to data, to knowledge guiding their analysis, to processing steps and to the analysis results.
At the same time, this session will discuss methods for improving image quality, which is affected by inaccuracies caused by image acquisition or processing. We are talking about eliminating visible defects (noise, blurred edges, etc.) and restoring the original information contained in the image.
The theoretical issues are at the core of many IPMU topics. Here the aim of the session would be address them in the specific context of image analysis, and more generally spatial information processing.
This special session is a joint event with the EUSFLAT Working Group on Soft Computing in Image Processing, which will encourage EUSFLAT members to contribute and promote discussions.
- Isabelle Bloch, Sorbonne Université, France
- Sébastien Destercke, Université de technologie de Compiègne, France
- Roman Malinowski, Centre National D’Etudes Spatiales, France
- Olivier Strauss, Université de Montpellier, France
- Humberto Bustince, Irina Perfilieva, Javier Montero as Coordinators of the EUSFLAT WG on Soft Computing in Image Processing, see https://www.eusflat.org/society-wg-scip.html
Examples of topics include:
- Representation models, types of uncertainties (epistemic, aleatoric, imprecision…).
- Reasoning under uncertainties or conflict, approximate reasoning.
- Integration of imprecision and uncertainty in the analysis process, either by reparing, by dealing with them (e.g. as metadata), by ignoring them, etc.
- Evaluation of uncertain results, making them useful to the users.
- Discussion about the necessity or opportunity to quantify uncertainty.
- Detect defects in digital images by estimating the degree of uncertainty of individual areas.
- Improving the quality of images by eliminating their defects.
SS13: Fuzzy Modelling and Control
Intelligent control systems encompass different techniques such as expert systems, fuzzy logic, neural networks, genetic algorithms, etc. However, fuzzy logic has proven to be the most widely used technique in industrial applications. The keys to this are its ability to represent the knowledge and experience of control/modelling experts and its ease of application. Another factor contributing to the deployment of fuzzy applications in industry is the increasing computational power of embedded systems. Thus, fuzzy inference systems are present at all levels of the automation pyramid and appear as a powerful tool for modelling, identifying and controlling complex plants.
The scope of the session will focus on the modelling and/or control of dynamic systems using fuzzy inference systems, including synergies with other techniques. Both relevant theoretical contributions and applications will be considered. The aim of this initiative is to bring together researchers in the field of intelligent systems who are interested in fuzzy logic modelling and/or control, and to gather the latest advances in their state of the art or applications. As such, the session aims to provide an overview of current high quality research in this area, while exploring new trends in fuzzy modelling and control methodologies.
Topics include, among others:
- Fuzzy control systems
- Fuzzy Identification and Fuzzy Modelling
- Hybrid-fuzzy modelling and identification
- Fuzzy clustering models
- Fuzzy modelling of high-dimensional systems
- Inverse model identification
- Juan Manuel Escaño / Universidad de Sevilla, Spain
- William D. Chicaiza / Universidad de Sevilla, Spain
SS14: EUSFLAT Working Group on Aggregation Operators
This special session aims at providing a platform for discussion of development of aggregation and fusion techniques and their applications in several fields
- Tomasa Calvo / University of Alcalá de Henares, Spain
- Anna Kolesárová / Slovak Technical University, Bratislava, Slovakia
- Radko Mesiar / Slovak Technical University, Bratislava, Slovakia
SS15: EUSFLAT Working Group on Fuzzy Logic-Based Decision Modeling in Economics and Social Sciences
The special session covers the topics of fuzzy logic and decision theory with an emphasis on applications in economics and social sciences. In the latter fields human perceptions play a very important role and the cross-fertilizations with the former fields has a huge
- Gisella Facchinetti / University of Salento, Italy;
- Mario Fedrizzi / University of Trento, Italy;
- Benedetto Matarazzo / University of Catania, Italy;
- Aldo Ventre / University of Napoli II, Italy
SS16: EUSFLAT Working Group on Genetic Fuzzy Systems
The field of Genetic Fuzzy Systems (GFS) has now reached a stage of maturity after the earliest papers were published sixteen years ago. The fusion of a population-based, robust search algorithm (the genetic algorithm, GA) with a representation that offers linguistic
interpretability (fuzzy systems) provides a powerful paradigm for computational intelligence research. Although the maturity of the GFS field means it is now being applied to an ever growing number of real-world applications, there are many basic issues yet to be resolved and there is an active and vibrant worldwide community of researchers
working on these issues.
- Brian Carse / University of the West of England, Bristol, UK;
- Jorge Casillas / University of Granada, Spain
SS17: EUSFLAT Working Group on Intuitionistic Fuzzy Sets: Theory, Applications and Related Topics
This special session aims at bringing together researches on foundations of the intuitionistic fuzzy sets and intuitionistic fuzzy logic, their extensions and relevant software implementation.
- Sotir Sotirov / “Prof. Asen Zlatarov” University, Burgas, Bulgaria;
- Vassia Atanassova / Bulgarian Academy of Sciences, Bulgaria;
- Peter Vassilev / Bulgarian Academy of Sciences, Bulgaria;
- Alžbeta Michalíková / Matej Bel University, Slovakia
SS18: EUSFLAT Working Group on Learning and Data Mining
Topics in the fields of machine learning and data mining have attracted considerable attention within the fuzzy set community in recent years. There are several motivations for combining tools and techniques from fuzzy set theory with learning and data mining methods, notably the following: Firstly, learning and adaptivity have become important aspects in fuzzy systems design, where data-driven approaches can complement knowledge-based methods in a reasonable way. Secondly, recent research has shown that fuzzy set theory can contribute to machine learning and data mining in a substantial way, e.g., in dealing with uncertainty in model induction or extracting vague patterns and relationships from data. The general goal of the working group is to promote research in the field of fuzzy machine learning and data mining. Moreover, the working group shall provide a forum for discussions on this topic and a repository for resources on fuzzy data mining, including, e.g., software and benchmark data sets.
- Plamen Angelov / Lancaster University, United Kingdom;
- Eyke Hüllermeier / Paderborn University, Germany;
- Frank Klawonn / University of Applied Sciences Braunschweig/Wolfenbüttel, Germany;
- Daniel Sánchez / Dept. Computer Science and A.I., University of Granada, Spain
SS19: EUSFLAT Working Group on Mathematical Fuzzy Logic
This special session is devoted to the most recent developments Mathematical Fuzzy Logic. Thus, to formal fuzzy logics from a mathematical point of view. Particular emphasis on theoretical advances related to many-valued logics, algebraic semantics, combinatorial aspects, topological and categorical methods, proof theory and game theory, many-valued computation.
A partial list of topics is the following:
- Algebraic semantics of many-valued logics
- Applications of many-valued logics to Formal Concept Analysis and Relational Methods
- Applications of many-valued logics to Fuzzy Sets and to Rough Sets
- Combinatorial or topological dualities
- Computational complexity of many-valued logics
- First-order many-valued logics, with applications to model theory and finite model theory
- Many-valued logics and automated reasoning
- Modal logic approaches to probability and uncertainty in many-valued logics
- Natural and alternative semantics for many-valued logics
- Proof theory for many-valued logics
- Subjective probability approaches to many-valued logics and non-classical events
- Matteo Bianchi – University of Milan, Italy
- Tommaso Flaminio – Artificial Intelligence Research Institute (IIIA – CSIC), Universitat
Autònoma de Barcelona, Spain;
- Amanda Vidal – Artificial Intelligence Research Institute (IIIA – CSIC), Universitat
Autònoma de Barcelona, Spain
SS20: EUSFLAT Working Group on Philosophical Foundations
The aim of the special session is to motivate philosophers, educators,and scientists, to approach the roots of Soft Computing, as well as its results in real applications.
- Rudolf Seising /Deutsches Museum, Deutschland;
- Marco Elio Tabacchi / Università degli Studi di Palermo, Italy;
- Settimo Termini / Università degli Studi di Palermo, Italy
SS21: EUSFLAT Working Group on Soft Computing in Database Management and Information Retrieval
Soft computing extends the facilities and effectiveness of database and information retrieval systems in order to make them better accessible and to cope with imperfections in information. The special session welcomes contributions on theoretical and applied research on soft computing in database management and information retrieval.
- Guy De Tré / Ghent University, Gent, Belgium;
- Gabriella Pasi / University of Milano, Italy;
- Sławomir Zadrożny / Polish Academy of Sciences, Warzawa, Poland