mlsanityData to 7 Oct 2026

Graph Neural Networks for Decentralized Controllers

arXiv 2003.10280 ↗First posted 23 Mar 2020cs.LG cs.SY eess.SYcited by 14

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Abstract (arXiv)

Dynamical systems comprised of autonomous agents arise in many relevant problems such as multi-agent robotics, smart grids, or smart cities. Controlling these systems is of paramount importance to guarantee a successful deployment. Optimal centralized controllers are readily available but face limitations in terms of scalability and practical implementation. Optimal decentralized controllers, on the other hand, are difficult to find. In this paper, we propose a framework using graph neural networks (GNNs) to learn decentralized controllers from data. While GNNs are naturally distributed architectures, making them perfectly suited for the task, we adapt them to handle delayed communications as well. Furthermore, they are equivariant and stable, leading to good scalability and transferability properties. The problem of flocking is explored to illustrate the potential of GNNs in learning decentralized controllers.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 5; 2023: 1; 2024: 0; 2025: 0; 2026: 1.

14 papers.

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  1. 2021Transferability Properties of Graph Neural Networkscited by 42
  2. 2022Graph Neural Networks in IoT: A Surveycited by 27
  3. 2021Decentralized Inference with Graph Neural Networks in Wireless Communication Systemscited by 18
  4. 2021Predicting Basin Stability of Power Grids using Graph Neural Networkscited by 10
  5. 2021Robust Graph Neural Networks via Probabilistic Lipschitz Constraintscited by 10
  6. 2021Communication Topology Co-Design in Graph Recurrent Neural Network Based Distributed Controlcited by 6
  7. 2022Privacy-Preserving Decentralized Inference with Graph Neural Networks in Wireless Networkscited by 5
  8. 2021Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Searchcited by 3
  9. 2022Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networkscited by 3
  10. 2022Towards dynamic stability analysis of sustainable power grids using graph neural networkscited by 2
  11. 2021Decentralized Statistical Inference with Unrolled Graph Neural Networkscited by 1
  12. 2022Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networkscited by 1
2 more
  1. 2023Transferability of Convolutional Neural Networks in Stationary Learning Taskscited by 1
  2. 2026A Gated Graph Neural Network Approach to Fast-Convergent Dynamic Average Estimationcited by 0