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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Veröffentlicht in:	Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems Jg. 2020-May; S. 1395
Hauptverfasser:	Tossou, Aristide, Dimitrakakis, Christos, Rzepecki, Jaroslaw, Hofmann, K.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	2020
Schlagworte:	Egalitarian bargaining solution Individual rationality Multi-armed bandits Safety
ISSN:	1558-2914, 1548-8403
Online-Zugang:	Volltext
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