Video/Webinars
Explainable AI for systems with functional safety requirements
Explainable AI (XAI) is vital for making AI decision-making processes transparent and understandable to human experts, and for ensuring safety and regulatory compliance.
Video/Webinars
Webinar "Industry-driven Use Cases"
AI4REALNET project covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic control), modelled by networks that can be simulated and traditionally operated by humans and where AI complements a
Video/Webinars
Webinar "Distributed and Hierarchical Reinforcement Learning"
In this webinar, AI4REALNET project provides an overview of two emerging topics in Reinforcement Learning (RL): Distributed RL and Hierarchical RL.
Case studies
Application of the ALTAI tool to power grids, railway network and air traffic management
This document presents the responses from industry (operators of critical infrastructures) to the Assessment List for Trustworthy AI (ALTAI) questionnaire for three domains and specific use cases: power grid, railway network, and air traffic manag
Video/Webinars
Towards functional safety management for AI-based critical systems
The webinar provides attendees with a comprehensive understanding of the challenges and opportunities associated with integrating AI into safety-critical systems.
White paper
Position paper on AI for the operation of critical energy and mobility network infrastructures
This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.