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Hubertus Franke

2 accepted papers

2023

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity

NeurIPS 2023poster

Multi-agent reinforcement learning (MARL) has primarily focused on solving a single task in isolation, while in practice the environment is often evolving, leaving many related tasks to be solved. In this paper, we investigate the benefits of meta-learning in solving multiple MARL tasks collectively…

Cited by 8SourcePDFScholar
2022

A Mean-Field Game Approach to Cloud Resource Management with Function Approximation

NeurIPS 2022accept

Reinforcement learning (RL) has gained increasing popularity for resource management in cloud services such as serverless computing. As self-interested users compete for shared resources in a cluster, the multi-tenancy nature of serverless platforms necessitates multi-agent reinforcement learning (M…

Cited by 26SourcePDFScholar