MAMBPO: Sample-efficient multi-robot reinforcement learning using learned world models

Multi-robot systems can benefit from reinforcement learning (RL) algorithms that learn behaviours in a small number of trials, a property known as sample efficiency. This research thus investigates the use of learned world models to improve sample efficiency. We present a novel multi-agent model-bas...

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Bibliographic Details

Published in:	Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 5635 - 5640
Main Authors:	Willemsen, Daniel, Coppola, Mario, de Croon, Guido C.H.E.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 27.09.2021
Subjects:	Intelligent robots Multi-robot systems Optimization Reinforcement learning Task analysis Training
ISSN:	2153-0866
Online Access:	Get full text
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