AI4REALNET

Abstract

AI4REALNET covers the perspective of AI-based solutions addressing critical systems (electricity, railway, and air traffic management) modelled by networks that can be simulated, and are traditionally operated by humans, and where AI systems complement and augment human abilities.

Our goals are: 1. To develop the next generation of decision-making methods powered by SL/RL, which aim at trustworthiness in AI-assisted human control with augmented cognition, hybrid human-AI co-learning, and autonomous AI, with the resilience, safety, and security of critical infrastructures as core requirements. 2. To boost the development and validation of novel AI algorithms by the consortium and AI community through existing open-source digital environments capable of emulating realistic scenarios of physical systems operation and human decision-making, enabling a direct assessment of AI-based decision quality.