Yannick Eich
Papers
1
Total Citations
8
H-Index
1
About
Yannick Eich is a researcher at the forefront of scalable multi-agent systems and reinforcement learning. His work addresses the fundamental challenge of coordinating decision-making in large-population environments, bridging theoretical control frameworks with practical algorithmic solutions. Eich’s most cited paper, “A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning” (2022, 8 citations), provides a comprehensive synthesis of this rapidly evolving field, connecting diverse applications from epidemiology and robotic swarms to economics and finance. This survey has become a key reference for researchers seeking to understand how mean-field approximations and decentralized learning can overcome the curse of dimensionality in multi-agent settings. By systematically mapping the landscape of large-population control and reinforcement learning, Eich has helped define the state of the art and identify critical open problems. His contributions are particularly valuable for students and engineers working on autonomous systems, smart grids, and distributed robotics, offering both a rigorous foundation and a practical roadmap for scalable multi-agent intelligence.
Research Focus
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Top Papers
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