Emergent communication of multimodal deep generative models based on Metropolis-Hastings naming game

Deep generative models (DGM) are increasingly employed in emergent communication systems. However, their application in multimodal data contexts is limited. This study proposes a novel model that combines multimodal DGM with the Metropolis-Hastings (MH) naming game, enabling two agents to focus join...

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Veröffentlicht in:	Frontiers in robotics and AI Jg. 10; S. 1290604
Hauptverfasser:	Hoang, Nguyen Le, Taniguchi, Tadahiro, Hagiwara, Yoshinobu, Taniguchi, Akira
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 31.01.2024
Schlagworte:	deep generative model emergent communication Metropolis-Hastings multimodal Robotics and AI symbol emergence variational autoencoder naming game Metropolis-Hastings symbol emergence multimodal variational autoencoder deep generative model emergent communication
ISSN:	2296-9144, 2296-9144
Online-Zugang:	Volltext
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