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pro vyhledávání: '"CUI Kai"'
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 assume perfectly rational agents and are hence implausible in many realist
Externí odkaz:
http://arxiv.org/abs/2411.07099
Autor:
Azem, Sharif, Scheunert, David, Li, Mengguang, Gehrunger, Jonas, Cui, Kai, Hochberger, Christian, Koeppl, Heinz
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 algorithms. To accomplish a broader range of tasks, there is a growing n
Externí odkaz:
http://arxiv.org/abs/2403.18703
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-actuation characteristic limits its applications, especially when it com
Externí odkaz:
http://arxiv.org/abs/2402.01477
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 significant progress towards solving these systems, solutions for many agents
Externí odkaz:
http://arxiv.org/abs/2401.12686
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 limited network resources. Evidently, network congestion is detrimental f
Externí odkaz:
http://arxiv.org/abs/2312.12977
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 policies for good performance. However, most existing scalable techniques, es
Externí odkaz:
http://arxiv.org/abs/2312.12973
Autor:
Cui, Kai, Dayanıklı, Gökçe, Laurière, Mathieu, Geist, Matthieu, Pietquin, Olivier, Koeppl, Heinz
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 homogeneous players that weakly influence each other, and cannot model m
Externí odkaz:
http://arxiv.org/abs/2312.10787
Autor:
Sreedhara, Akash Kopparam, Padala, Deepesh, Mahesh, Shashank, Cui, Kai, Li, Mengguang, Koeppl, Heinz
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 payloads by multiple drones is another important area of recent research. H
Externí odkaz:
http://arxiv.org/abs/2310.02726
Recent reinforcement learning (RL) methods have achieved success in various domains. However, multi-agent RL (MARL) remains a challenge in terms of decentralization, partial observability and scalability to many agents. Meanwhile, collective behavior
Externí odkaz:
http://arxiv.org/abs/2307.06175
Autor:
Cui, Kai, Baumgärtner, Lars, Yilmaz, Burak, Li, Mengguang, Fabian, Christian, Becker, Benjamin, Xiang, Lin, Bauer, Maximilian, Koeppl, Heinz
Both data ferrying with disruption-tolerant networking (DTN) and mobile cellular base stations constitute important techniques for UAV-aided communication in situations of crises where standard communication infrastructure is unavailable. For optimal
Externí odkaz:
http://arxiv.org/abs/2307.02988