This Topical Area covers a wide range of core aspects of intelligence systems, with a particular focus on AI. Nowadays, AI is usually perceived as closely related to the data, therefore, the scope of this Topical Area includes, among others, elements of machine learning, data science, and big data processing, with important emerging aspects such as interactive learning and human-centered AI, as well as interpretable learning, explainable AI, and trustworthiness. Furthermore, since the realm of AI is far richer, the ultimate goal of this Topical Area is to show relationships between all of the currently pursued AI subareas, emphasizing a cross-disciplinary nature of various research branches. From the perspective of the general scope of FedCSIS, this Topical Area embraces AI methods and examples of their applications in different practical fields.

The aim of this Topical Area is to bring together scientists and practitioners to discuss their latest results and ideas in all areas of Artificial Intelligence. We hope that successful applications presented here will be of interest to researchers who want to know about both theoretical advances and latest applied developments in AI.

Papers related to theories, methodologies, and applications in science and technology in the field of AI are especially solicited. Topics covering industrial applications and academic research are included, but not limited to:

1. Reasoning, Knowledge Representation, and Decision Making
Decision Support
Fuzzy Sets and Soft Computing
Rough Sets and Approximate Reasoning
Bayesian Networks and Bayesian Reasoning
Case-based Reasoning and Similarity

2. Machine Learning, Data, and Knowledge Discovery
Machine Learning
Neural Networks and Deep Learning
Reinforcement Learning
Evolutionary Algorithms and Evolutionary Computation
Generative AI and Diffusion Models
Zero-Shot and Few-Shot Learning
Foundation Models and Large Language Models (LLMs)
Quantum Machine Learning
Federated Learning and Privacy-Preserving AI
Data Mining and Knowledge Discovery
Data Modeling and Feature Engineering
Data Integration and Information Fusion

3. Applications, Systems, and Domains
Hybrid and Hierarchical Intelligent Systems
Web Mining and Social Networks
Business Intelligence and Online Analytics
Robotics and Cyber-Physical Systems
AI for Combinatorial Games, Video Games and Serious Games
AI-centered Systems and Large-Scale Applications
AI for Autonomous Systems and Self-Driving Technologies
Digital Twins and Virtual Environments

4. Explainability, Ethics, and Governance
Explainable and Interpretable AI (XAI)
Human-Centered AI

Topical Area Curators
Eftim Zdravevski, University of Saints Cyril and Methodius, Macedonia
Piotr Artiemjew, University of Warmia and Mazury, Poland
Roberto Corizzo, American University, USA
Zaineb Chelly-Dagdia, UVSQ - Paris Saclay University, France

Contact: aaia@fedcsis.org


Related Thematic Sessions: The following Thematic Tracks at IEEE FedCSIS are related to this Topical Area:

AgriAI – AI in Agriculture
CNLPS – Challenges for Natural Language Processing
CO – Computational Optimization
SLSAS – Self Learning and Self Adaptive Systems

Submission rules
Authors should submit their papers as Postscript, PDF or MSWord files.
The total length of a paper should not exceed 12 pages IEEE style (including tables, figures and references). More pages can be added, for an additional fee. IEEE style templates are available.
Papers will be refereed and accepted on the basis of their scientific merit and relevance to the Topical Area.
Preprints containing accepted papers will be published online.
Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore® database.
Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site.
Conference proceedings will be submitted for indexation according to information here.
Organizers reserve right to move accepted papers between FedCSIS Sessions.