Special Sessions ESCIM2024.
Besides the Workshop DigForASP, this edition the symposium will include three Special Sessions on particular topics. You can select the special session in the submission platform: https://cmt3.research.microsoft.com/ESCIM2024/Submission/Index
SS1. Decision and Optimization models applied to Logistics and Transport.
SS2. Recent trends in knowledge representation and modelling
SS3. Rough Sets and Information Granulation
The submission of short abstracts (1 or 2 pages) on a relevant topic to the Special Sessions is open until February 11th.
Special Session 1: Decision and Optimization models applied to Logistics and Transport.
Organizers: Julio Alberto López-Gómez, David Muñoz-Valero, Juan Moreno-García (all the organizarers are with University of Castilla la Mancha, Spain).
Description: Traditionally, logistics and transport are two important application fields that have attracted a lot of research efforts due to their large impact on the population in the economic and welfare fields. Decision theory and optimisation are two closely related areas that, separately or jointly, allow for the efficient solution of problems in both areas.
The aim of this special session is twofold: on the one hand, to bring together researchers and research groups working in the fields of logistics and transport by implementing decision models and solving optimisation problems. On the other hand, the aim is to include papers presenting novel approaches or applications within the fields of logistics and transport using advanced decision models and modern optimisation techniques.
Keywords and related topics:
- Decision models applied to logistic and transport problems.
- Approximate reasoning
- Simulation models in logistic and transport: applications
- Advanced optimization techniques applied to logistic and transport problems.
- Machine Learning and Deep Learning models in logistic and transport
- Data-driven models for decision-making and/or optimization
Contact:
- «Julio Alberto López Gómez» JulioAlberto.Lopez(at)uclm.es
- «David Muñoz Valero» David.Munoz(at)uclm.es
- «Juan Moreno García» Juan.Moreno(at)uclm.es
Special Session 2: Recent trends in knowledge representation and modelling.
Organizers: Roberto García-Aragón (Univ. of Cádiz, Spain), David Lobo (Univ. of Cádiz, Spain), Manuel Ojeda-Hernández (Univ. of Málaga, Spain)
Description: The Special Session is focused on theoretical and applied tools for representing and modelling information. In particular, our interest is in the direction of recent techniques for dealing with uncertainty. In this sense, Formal Conceptual Analysis, Logic Programming and Fuzzy Relation Equations, together with their fuzzy extensions, arise as reliable tools for dealing with knowledge obtained from databases that are uncertain in some way, such as incomplete, imprecise, ambiguous, graded. These are some of the highlighted topics of interest in the session, but contributions related to other fields are also welcome.
Keywords and related topics:
- Formal Concept Analysis
- Logic Programming
- Fuzzy Relation Equations
Contact:
- Roberto García-Aragón: roberto.aragon(at)uca.es
- David Lobo: david.lobo(at)uca.es
- Manuel Ojeda-Hernández: manuojeda(at)uma.es
Special Session 3: Rough Sets and Information Granulation
Organizers: Eloísa Ramírez-Poussa (Univ. of Cádiz, Spain),Dominik Ślęzak (Univ. of Warsaw, Poland), Jarosław Wąs (AGH Univ. of Science and Technology, Poland).
Description:
The theory of Rough Sets serves as an efficient framework for data / information / knowledge representation and exploration. Its focus is on simplicity and interpretability of decision and computational models, even if such models refer to big and complex data. Rough-set-based algorithms and models operate on granular data representations (partitions, coverings, fuzzy similarities etc.) which brings us to a broader topic of applications of Granular Computing and Information Granulation in different domains of Computer Science, including AI/ML. Consequently, this special session aims at discussing various approaches that utilize the paradigms of Rough Sets and Information Granulation to produce simple solutions for complex data-driven problems.
Keywords and related topics:
- Rough Set Theory and Applications
- Information and Data Granulation
- Rough Clustering and Computing
- Rough-Fuzzy-Granular Hybridizations
- Hierarchical and Multimodal Data Mining
- Interpretable and Interactive Data Mining
- ML Model Compaction/Simplification
- Data-Driven Systems and Simulations
Contact:
- Eloísa Ramírez-Poussa: eloisa.ramirez(at)uca.es
- Dominik Ślęzak: slezak(at)mimuw.edu.pl
- Jarosław Wąs: jarek(at)agh.edu.pl