Displaying 105 resources

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 and

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.
For both DRL and HRL, a general definition of the paradigm is provided, discussing the learning object


Application of the ALTAI tool to power grids, railway network and air traffic management

Uncertainty-Based Learning of a Lightweight Model for Multimodal Emotion Recognition



Towards functional safety management for AI-based critical systems


Position paper on AI for the operation of critical energy and mobility network infrastructures

An overview of key trustworthiness attributes and KPIs for trusted ML-based systems engineering
When deployed, machine-learning (ML) adoption depends on its ability to actually deliver the expected service safely, and to meet user expectations in terms of quality and continuity of service.