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Learning Brain-Storming with Multiagent Multi-Armed Bandits
Alejandra López de Aberasturi Gómez, Jordi Sabater-Mir, Carles Sierra
109 - 112
10.3233/FAIA240419
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 390: Artificial Intelligence Research and Development
Abstract

We formalise human teamwork in tasks involving judgment as a public goods game. Our focus is on tasks where members’ contributions are combined through weighted averaging, such as brain-storming. Using a multiagent system, we examine the alignment between learned agent strategies and Nash Equilibria. Overall, our results demonstrate that our multiagent system effectively approximates the Nash Equilibria of the game.

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