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Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control
The aim of this work is to suggest architectures that inherit the computational efficiency and scalability of Differential Dynamic Programming (DDP) and the distributed nature of the Alternating Direction Method of Multipliers (ADMM).
Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM
In this work, we propose a novel safe and scalable decentralized solution for multi-agent control in the presence of stochastic disturbances.
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