Recursive Spoken Instruction-Based One-Shot Object and Action Learning

被引：0
|
作者：
Scheutz, Matthias [1 ]
Krause, Evan [1 ]
Oosterveld, Bradley [1 ]
Frasca, Tyler [1 ]
Platt, Robert [2 ]
机构：
[1] Tufts Univ, Human Robot Interact Lab, Medford, MA 02111 USA
[2] Northeastern Univ, Boston, MA 02115 USA
来源：
PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2018年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Learning new knowledge from single instructions and being able to apply it immediately is highly desirable for artificial agents. We provide the first demonstration of spoken instruction-based one-shot object and action learning in a cognitive robotic architecture and briefly discuss the architectural modifications required to enable such fast learning, demonstrating the new capabilities on a fully autonomous robot.
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收藏
页码：5354 / 5358
页数：5
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