2 citations · 4 across the 15 of their papers we have counts for
4 papers · 1 filter
Learning Mean Field Control on Sparse Graphs
Christian Fabian, Kai Cui, Heinz Koeppl
Large agent networks are abundant in applications and nature and pose difficult challenges in the field of multi-agent reinforcement learning (MARL) due to their computational and…
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
Christian Fabian, Kai Cui, Heinz Koeppl
Learning the behavior of large agent populations is an important task for numerous research areas. Although the field of multi-agent reinforcement learning (MARL) has made signific…
Collaborative Optimization of the Age of Information under Partial Observability
Anam Tahir, Kai Cui, Bastian Alt +2
The significance of the freshness of sensor and control data at the receiver side, often referred to as Age of Information (AoI), is fundamentally constrained by contention for lim…
Learning to Cooperate and Communicate Over Imperfect Channels
Jannis Weil, Gizem Ekinci, Heinz Koeppl +1
Information exchange in multi-agent systems improves the cooperation among agents, especially in partially observable settings. In the real world, communication is often carried ou…