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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Bibliographic Details

Published in:	Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 4583 - 4588
Main Authors:	Marchesini, Enrico, Farinelli, Alessandro
Format:	Conference Proceeding
Language:	English
Published:	IEEE 27.09.2021
Subjects:	Computational modeling Computer architecture Estimation Navigation Reinforcement learning Task analysis Training
ISSN:	2153-0866
Online Access:	Get full text
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