Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation

We study the problem of multi-robot mapless navigation in the popular Centralized Training and Decentralized Execution (CTDE) paradigm. This problem is challenging when each robot considers its path without explicitly sharing observations with other robots and can lead to non-stationary issues in De...

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Vydané v:	Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems s. 4583 - 4588
Hlavní autori:	Marchesini, Enrico, Farinelli, Alessandro
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 27.09.2021
Predmet:	Computational modeling Computer architecture Estimation Navigation Reinforcement learning Task analysis Training
ISSN:	2153-0866
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