Structurally Guided Task Decomposition in Spatial Navigation Tasks

Ruiqi He, Carlos G. Correa, Thomas L. Griffiths, Mark K. Ho

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)23512-23513
Number of pages2
JournalProceedings of the AAAI Conference on Artificial Intelligence
Issue number21
StatePublished - Mar 25 2024
Event38th AAAI Conference on Artificial Intelligence, AAAI 2024 - Vancouver, Canada
Duration: Feb 20 2024Feb 27 2024

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


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