Scope & Topics

Scope

Nowadays, Artificial Intelligence has become an enabling technology that pervades many aspects of our daily life. At the forefront of this advancement are data-driven technologies like machine learning. However, as the role of Artificial Intelligence becomes more and more important, so does the need for reliable solutions to several issues that go well beyond technological aspects:

  • How can we make automated agents justify their actions? and how to make them accountable for these actions?

  • What will be the social acceptance of automated agents, possibly embodied (robots), in their interaction with people?

  • How will automated agents be made aware of the whole spectrum of human nonverbal communication, so as to take it into account and avoid missing crucial messages?

  • Is it possible to avoid amplifying human biases and ensure fairness in decisions that have been taken automatically?

  • How can we enable collaborative intelligence amongst humans and machines?

Purely data-driven technologies are showing their limits precisely in these areas. There is a growing need for methods that, in a tight interaction with them, allow different degrees of control over the several facets of automated knowledge processing. The diversity and complementarity of Computational Intelligence techniques in addressing these issues is playing a crucial role.

The 13th International Workshop on Fuzzy Logic and Applications (WILF 2020) covers all topics in theoretical, experimental and applied Fuzzy and Computational Intelligence techniques and systems. It is aimed to bring together researchers and developers from both academia and industry to report on the latest scientific and theoretical advances in this field, and to demonstrate the state-of-the-art systems.

The WILF series is also aimed to highlight connections and synergies of Fuzzy Sets Theory with other Computational Intelligence paradigms (e.g., Deep and Shallow Neural Networks, Evolutionary Computation, Support Vector Machines, Natural Computing, Quantum Computing), Machine Learning approaches (e.g., Decision Tree, Support Vector Machines, Random Forest, Naive Bayes), Cognitive Science (e.g., Psychology, Philosophy, Neuroscience, Linguistics) and Explainable Artificial Intelligence, in order to reach a better understanding of both natural and artificial complex systems as well as computing systems, inspired by nature, which are able to solve complex problems.

Topics

Topics of interest include, but are not limited to:

Theory and Methodology

Fuzzy Sets; Rough Sets; Possibility Theory; Fuzzy Logic; Fuzzy Systems; Neuro-Fuzzy Systems; Interpretability of Fuzzy Systems; Representation of Vague and Imprecise Knowledge; Fuzzy Evolutionary Algorithms; Fuzzy Image Processing; Fuzzy Pattern Recognition; Fuzzy Data Fusion; Intuitionistic Fuzzy Sets; Fuzzy Approaches for High Dimensional Data Analysis.

Applications

Industry 4.0; Smart City; Healthcare; Ambient Assisted Living; Bioinformatics; Broadcasting; Control; Communications; Information Retrieval; Intelligent Resource Management; Knowledge Management; Health; Opto-mechatronics; Recommendation and Personalization; Remote Sensing; Robotics; Semantic Web; Speech Analysis; Television; Telepresence; User profiling; Virtual Reality; Activity Analysis and Recognition; Emotional Computing; Complex Networks Analysis.

Implementations

Fuzzy Systems Software; Analog and Digital Circuits and Systems; Programmable Processors; Soft Grid Computing; Platforms and frameworks; Commercial Software.