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Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between...

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Detalhes bibliográficos
Publicado no:Front Neurorobot
Main Authors: Taniguchi, Akira, Taniguchi, Tadahiro, Cangelosi, Angelo
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2017
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5742219/
https://ncbi.nlm.nih.gov/pubmed/29311888
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnbot.2017.00066
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