English

Structurally guided task decomposition in spatial navigation tasks

Machine Learning 2023-10-04 v1

Abstract

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 a wide range of simple planning problems by adding structure information to the task to facilitate planning in more complex tasks. The extended model was then 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.

Keywords

Cite

@article{arxiv.2310.02221,
  title  = {Structurally guided task decomposition in spatial navigation tasks},
  author = {Ruiqi He and Carlos G. Correa and Thomas L. Griffiths and Mark K. Ho},
  journal= {arXiv preprint arXiv:2310.02221},
  year   = {2023}
}
R2 v1 2026-06-28T12:39:39.328Z