Scientific Papers

Discover AI4REALNET research

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Explore HERE the AI4REALNET research.

Document

Fault Detection for Agents in Power Grid Topology Optimization: A Comprehensive Analysis

Date

11/10/2024

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Document

Pioneering roadmap for ML-driven algorithmic advancements in electrical networks

Date

11/10/2024

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Document

State and Action Factorization in Power Grids

Date

11/10/2024

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Multi-Objective Reinforcement Learning for Power Grid Topology Control

Date

07/02/2025

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Document

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning

Date

12/02/2025

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Document

How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach

Date

12/02/2025

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Document

Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning

Date

13/02/2025

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Document

Imitation Learning for Intra-Day Power Grid Operation through Topology Actions

Date

27/03/2025

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On the Definition of Robustness and Resilience of AI Agents for Real-time Congestion Management

Date

14/05/2025

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Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control

Date

14/05/2025

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User experience evaluation of an AI-based decision support tool for power grid congestion management

Date

03/09/2025

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Document

Human-AI interaction in safety-critical network infrastructures

Date

24/09/2025

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Document

Learning Topology Actions for Power Grid Control: A Graph-Based Soft-Label Imitation Learning Approach

Date

13/10/2025

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Document

Generation of Power Network Operating Scenarios for an AI-friendly Digital Environment

Date

13/10/2025

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Document

A Conceptual Framework for AI-based Decision Systems in Critical Infrastructures

Date

13/10/2025

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Study Design and Demystification of Physics Informed Neural Networks for Power Flow Simulation

Date

13/10/2025

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Document

Applying Job Design Criteria for Effective Human-AI Collaboration

Date

13/10/2025

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Document

Learned Representations Enhance Multi Agent Path Planning

Date

13/10/2025

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Document

Power Grid Control with Graph-Based Distributed Reinforcement Learning

Date

13/10/2025

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Document

Continuous Assessment Driven Requirements Elicitation For Trustworthy AI Systems

Date

13/10/2025

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Document

Evolving power system operator rules for real-time congestion management

Date

27/01/2026

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Document

Current and Future Applications of Artificial Intelligence in Power Systems: A Critical Appraisal

Date

10/02/2026

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Document

The Supportive AI Framework: From recommending to supporting

Date

13/02/2026

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Document

Graph reinforcement learning for power grids: A comprehensive survey

Date

13/02/2026

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Document

Toward a Holistic Framework for Human-AI Collaboration in Safety-Critical Systems

Date

11/03/2026

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Document

Human-AI Interaction and Visualization Perspectives on ADR

Date

11/03/2026

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Document

Towards Autonomous Railway Operations: A Semi-Hierarchical Deep Reinforcement Learning Approach to the Vehicle Rescheduling Problem

Date

12/05/2026

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Document

Understanding OPF Redispatch Actions through LLM-Assisted Counterfactual Analysis

Date

30/06/2026

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Document

Uncertainty quantification and failure prediction for AI-based congestion management

Date

30/06/2026

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Document

Interactive Dynamic Airspace Sectorization through Human-in-the-Loop Optimization

Date

30/06/2026

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Document

A Methodical Approach to AI-Supported Human Learning in Complex Task Environments

Date

03/07/2026

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Document

The stochastic nature of machine learning and its implications for high-consequence AI

Date

03/09/2026

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Document

Graph Neural Networks for Transmission Grid Topology Control: Busbar Information Asymmetry and Heterogeneous Representations

Date

07/10/2026

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Document

Designing for Human-AI Teaming in Power System Control Room Decision Support

Date

20/10/2026

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Document

AI-Driven Assistant for Critical Infrastructures Human Operators: an Online Cognitive Performance and Stress Monitoring Platform Based on ECG Morphology and Heart Rate Variability

Date

02/11/2026

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