A novel individually rational objective in multi-agent multi-armed bandits: Algorithms and regret bounds

We study a two-player stochastic multi-armed bandit (MAB) problem with different expected rewards for each player, a generalisation of two-player general sum repeated games to stochastic rewards. Our aim is to find the egalitarian bargaining solution (EBS) for the repeated game, which can lead to mu...

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Bibliographic Details

Published in:	Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems Vol. 2020-May; p. 1395
Main Authors:	Tossou, Aristide, Dimitrakakis, Christos, Rzepecki, Jaroslaw, Hofmann, K.
Format:	Conference Proceeding
Language:	English
Published:	2020
Subjects:	Egalitarian bargaining solution Individual rationality Multi-armed bandits Safety
ISSN:	1558-2914, 1548-8403
Online Access:	Get full text
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