Self Learning and Self Adaptive Systems
(SLSAS)

Kraków, Poland, 14-17 September, 2025

The proposed thematic session is focused on advanced Artificial Intelligence (AI) techniques and their applications in various fields. One of the advanced forms of AI methods is the Reinforcement Learning (RL) algorithms. RL or Self-learning systems are AI agents able to acquire and renew knowledge over time without hard coding. These are adaptive systems whose functions improve by a learning process based -typically- on the method of trial and error. A self-learning system initially interacts with its users or surrounding environment by attempting and observing the changes produced by its actions. This session will focus on the design, implementation, and exploitation of self-learning features within an Intelligent Environment or some of its components. The thematic session will represent an opportunity for academia and industry to debate the state-of-the-art challenges and open issues.

Topics

The thematic session aims to consider methodological work and self-learning applications. In particular, works based on AI technologies, including Machine Learning, Reinforcement Learning, and Deep Learning. In this context, we are looking for contributions covering one or more of the following topics:

AI applications in 5G systems and beyond
AI-enabled smart technologies for human-centered IoT systems
AI-based eHealth systems
Deep learning-driven distributed communication systems
AI-enabled personalized systems for education
Blockchain-enabled communication systems
Behavior analysis of patients, seniors, and others
Softwarized UAV network management for next-generation internet-based communities
Edge- and 6G-driven ubiquitous wireless communication
AmI security and privacy models for healthcare applications

Thematic Session organizers

Muddasar Naeem - Researcher and Contract professor at Università Giustino Fortunato - Benevento Italy. Website link: https://www.unifortunato.eu/docente/prof-naeem-muddasar/
Antonio Coronato - Full Professor at Università Giustino Fortunato - Benevento, Italy. Website link: https://www.unifortunato.eu/docente/prof-antonio-coronato/
Syed Tahir Hussain Rizvi - Machine Learning Engineer at Wenn AsA, Sandnes, Norway.

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.

Best Paper

There is a possibility that the best paper of the Thematic Session will be submitted to the Special Issue “AI-Based Innovations in 5G Communications and Beyond”. (https://www.mdpi.com/journal/network/special_issues/W0P92SZ9XF)