Structured Power Grid Simulation Dataset for Machine Learning: Failure and Survival Events in Grid2Op's L2RPN WCCI 2022 Environment
This dataset was developed for and used in the paper titled "Fault Detection for Agents in Power Grid Topology Optimization: A Comprehensive Analysis" by Malte Lehna, Mohamed Hassouna, Dmitry Degtyar, Sven Tomforde, and Christoph Scholz,

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

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.

Holistic framework for AI in critical network infrastructures
This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator

AI for Teachers
AI for Teachers is a website dedicated to supporting the integration of Artificial Intelligence knowledge throughout K-12 learning.

Don’t ask if AI is good or fair, ask how it shifts power
Opinion piece by Pratyusha Kalluri in Nature