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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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| Gepubliceerd in: | Front Neurorobot |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Frontiers Media S.A.
2017
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| Onderwerpen: | |
| Online toegang: | 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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