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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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Bibliografske podrobnosti
izdano v:Front Neurorobot
Main Authors: Baldassarre, Gianluca, Lord, William, Granato, Giovanni, Santucci, Vieri Giuliano
Format: Artigo
Jezik:Inglês
Izdano: Frontiers Media S.A. 2019
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC6676802/
https://ncbi.nlm.nih.gov/pubmed/31402859
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnbot.2019.00045
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