2 citations · 4 across the 15 of their papers we have counts for
15 papers
Task-Adaptive Design of Modular Aerial Manipulators Under Airflow Exposure Constraints
Mengguang Li, Heinz Koeppl
Aerial manipulation with multirotor platforms enables physical interaction in complex environments, but rotor-induced airflow remains a critical limitation for tasks involving airf…
Approximately Solving Continuous-Time Mean Field Games with Finite State Spaces
Yannick Eich, Christian Fabian, Kai Cui +1
Mean field games (MFGs) offer a powerful framework for modeling large-scale multi-agent systems. This paper addresses MFGs formulated in continuous time with discrete state spaces,…
Fluctuation induced network patterns in active matter with spatially correlated noise
Sebastian Fehlinger, Kai Cui, Arooj Sajjad +2
Fluctuations play a central role in many fields of physics, from quantum electrodynamics to statistical mechanics. In active matter physics, most models focus on thermal fluctuatio…
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…
Bounded Rationality Equilibrium Learning in Mean Field Games
Yannick Eich, Christian Fabian, Kai Cui +1
Mean field games (MFGs) tractably model behavior in large agent populations. The literature on learning MFG equilibria typically focuses on finding Nash equilibria (NE), which assu…
FPGA-Based Neural Thrust Controller for UAVs
Sharif Azem, David Scheunert, Mengguang Li +4
The advent of unmanned aerial vehicles (UAVs) has improved a variety of fields by providing a versatile, cost-effective and accessible platform for implementing state-of-the-art al…
A Modular Aerial System Based on Homogeneous Quadrotors with Fault-Tolerant Control
Mengguang Li, Kai Cui, Heinz Koeppl
The standard quadrotor is one of the most popular and widely used aerial vehicle of recent decades, offering great maneuverability with mechanical simplicity. However, the under-ac…
Approximate Control for Continuous-Time POMDPs
Yannick Eich, Bastian Alt, Heinz Koeppl
This work proposes a decision-making framework for partially observable systems in continuous time with discrete state and action spaces. As optimal decision-making becomes intract…
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 Discrete-Time Major-Minor Mean Field Games
Kai Cui, Gökçe Dayanıklı, Mathieu Laurière +3
Recent techniques based on Mean Field Games (MFGs) allow the scalable analysis of multi-player games with many similar, rational agents. However, standard MFGs remain limited to ho…
Sparse Mean Field Load Balancing in Large Localized Queueing Systems
Anam Tahir, Kai Cui, Heinz Koeppl
Scalable load balancing algorithms are of great interest in cloud networks and data centers, necessitating the use of tractable techniques to compute optimal load balancing policie…
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…
A Survey of Confidence Estimation and Calibration in Large Language Models
Jiahui Geng, Fengyu Cai, Yuxia Wang +3
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks in various domains. Despite their impressive performance, they can be unreliable…
Optimal Collaborative Transportation for Under-Capacitated Vehicle Routing Problems using Aerial Drone Swarms
Akash Kopparam Sreedhara, Deepesh Padala, Shashank Mahesh +3
Swarms of aerial drones have recently been considered for last-mile deliveries in urban logistics or automated construction. At the same time, collaborative transportation of paylo…