An Embodied Agent Learning Affordances With Intrinsic Motivations and Solving Extrinsic Tasks With Attention and One-Step Planning

We propose an architecture for the open-ended learning and control of embodied agents. The architecture learns action affordances and forward models based on intrinsic motivations and can later use the acquired knowledge to solve extrinsic tasks by decomposing them into sub-tasks, each solved with o...

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Detalles Bibliográficos
Autores principales: Baldassarre, Gianluca, Lord, William, Granato, Giovanni, Santucci, Vieri Giuliano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676802/
https://www.ncbi.nlm.nih.gov/pubmed/31402859
http://dx.doi.org/10.3389/fnbot.2019.00045

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676802/
https://www.ncbi.nlm.nih.gov/pubmed/31402859
http://dx.doi.org/10.3389/fnbot.2019.00045

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