Hierarchical multi-agent reinforcement learning with graph neural networks for cross scale ecosystem protection

We propose a hierarchical Multi Agent Reinforcement Learning (MARL) framework augmented with Graph Neural Networks (GNNs) to address the challenges of cross-scale ecological interactions in ecosystem protection.

Publication Details

Journal
Journal of Artificial Intelligence & Robotics
Published
2025-06-17
DOI
https://doi.org/10.52768/3067-7947/1020
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
0.00
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article

Hierarchical multi-agent reinforcement learning with graph neural networks for cross scale ecosystem protection

Journal of Artificial Intelligence & Robotics
Reinforcement Learning in Robotics
article

Hierarchical multi-agent reinforcement learning with graph neural networks for cross scale ecosystem protection

article en

Abstract

We propose a hierarchical Multi Agent Reinforcement Learning (MARL) framework augmented with Graph Neural Networks (GNNs) to address the challenges of cross-scale ecological interactions in ecosystem protection.

Journal of Artificial Intelligence & RoboticsVol. 2(1)
Life in Land
Openalex Percentile: Top 24%
Reinforcement Learning in Robotics
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Hierarchical multi-agent reinforcement learning with graph neural networks for cross scale ecosystem protection · Journal of Artificial Intelligence & Robotics (2025) | TGRS Research Map | TGRS