Topical Area 1: Advanced Artificial Intelligence Approaches
(AAIA)

Riga, Latvia, 23-26 August, 2026

Scope and Objectives

The Advanced Artificial Intelligence Approaches (AAIA) Topical Area focuses on foundational and methodological research directions in Artificial Intelligence, covering theoretical developments as well as systematically grounded applications. The renaming from Advanced Artificial Intelligence Applications reflects a shift toward core AI approaches, with emphasis on novel models, learning paradigms, reasoning frameworks, and their formal or empirical analysis. Contemporary AI research increasingly integrates data-driven learning with symbolic reasoning, probabilistic modeling, optimization methods, and human-centered perspectives. Consequently, the scope of AAIA includes machine learning, data science, and intelligent systems, while addressing emerging challenges such as foundation models, explainability, trustworthiness, and human–AI interaction. The objective of this Topical Area is to highlight relationships between diverse AI subfields, encourage cross-disciplinary research, and present advanced AI approaches that can be composed into hybrid, hierarchical, and interpretable systems. Contributions may focus on theory, methodology, or applications, provided that they advance understanding of intelligent system design or behavior.

AAIA aims to bring together researchers and practitioners to discuss recent advances, open challenges, and future directions in Artificial Intelligence, promoting dialogue between theoretical research, methodological innovation, and real-world deployment.

Topics

Papers related to theories, methodologies, and advanced applications of Artificial Intelligence are especially solicited. Topics include, but are not limited to:

Reasoning, Knowledge Representation, and Decision Making

Reasoning under uncertainty
Knowledge representation and symbolic AI
Approximate and non-monotonic reasoning
Decision-making models and decision support systems

Computational Intelligence and Soft Computing

Fuzzy sets and fuzzy reasoning
Rough sets and granular computing
Soft computing and hybrid reasoning frameworks

Probabilistic and Statistical AI

Bayesian networks and Bayesian reasoning
Probabilistic graphical models
Uncertainty modeling and inference

Machine Learning and Data-Centric AI

Machine learning theory and algorithms
Data mining and knowledge discovery
Feature engineering and data modeling
Data integration and information fusion

Advanced Learning Paradigms

Neural networks and deep learning
Reinforcement learning
Evolutionary algorithms and evolutionary computation
Zero-shot and few-shot learning
Generative AI and diffusion models

Foundation Models and Emerging AI Approaches

Foundation models and large language models
Multimodal learning
Federated learning and privacy-preserving AI
Quantum machine learning

Hybrid, Large-Scale, and Intelligent Systems

Hybrid and hierarchical intelligent systems
AI-centered systems and large-scale AI applications
Web mining and social networks
Business intelligence and online analytics

Autonomous, Cyber-Physical, and Interactive Systems

Robotics and cyber-physical systems
AI for autonomous systems and self-driving technologies
Digital twins and virtual environments
AI for combinatorial games, video games, and serious games

Explainability, Ethics, and Human-Centered AI

Explainable and interpretable AI
Trustworthy and responsible AI
Human-centered AI and interactive learning

Topical Area Curators

Eftim Zdravevski University Ss. Cyril and Methodius, Macedonia
Piotr Artiemjew University of Warmia and Mazury, Poland
Roberto Corizzo American University, USA
Zaineb GARCIA Chelly-Dagdia University of Lille, France

Contact: aaia@fedcsis.org

Related Thematic Sessions

The following Thematic Tracks are related to this Topical Area:

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 here.
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.

Authors of selected papers relevant to this Topical Area will be invited to submit extended versions of their papers to the Human-Centric Intelligent Systems journal.