Structurally Guided Task Decomposition in Spatial Navigation Tasks (Student Abstract)

被引：0
|
作者：
He, Ruiqi [1 ]
Correa, Carlos G. [2 ]
Griffiths, Thomas L. [3 ,4 ]
Ho, Mark K. [5 ]
机构：
[1] Max Planck Inst Intelligent Syst, Tubingen, Germany
[2] Princeton Univ, Princeton Neurosci Inst, Princeton, NJ USA
[3] Princeton Univ, Dept Psychol, Princeton, NJ USA
[4] Princeton Univ, Dept Comp Sci, Princeton, NJ USA
[5] Stevens Inst Technol, Dept Comp Sci, Hoboken, NJ USA
来源：
THIRTY-EIGTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 21 | 2024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：
How are people able to plan so efficiently despite limited cognitive resources? We aimed to answer this question by extending an existing model of human task decomposition that can explain simple planning problems by adding structure information to facilitate planning in more complex tasks. The extended model was applied to a more complex planning domain of spatial navigation. Our results suggest that our framework can correctly predict the navigation strategies of the majority of the participants in an online experiment.
引用
收藏
页码：23512 / 23513
页数：2
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