Resource-rational Task Decomposition to Minimize Planning Costs

July 27, 2020 Β· Declared Dead Β· πŸ› Annual Meeting of the Cognitive Science Society

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Authors Carlos G. Correa, Mark K. Ho, Fred Callaway, Thomas L. Griffiths arXiv ID 2007.13862 Category cs.AI: Artificial Intelligence Cross-listed cs.LG Citations 21 Venue Annual Meeting of the Cognitive Science Society Last Checked 4 months ago
Abstract
People often plan hierarchically. That is, rather than planning over a monolithic representation of a task, they decompose the task into simpler subtasks and then plan to accomplish those. Although much work explores how people decompose tasks, there is less analysis of why people decompose tasks in the way they do. Here, we address this question by formalizing task decomposition as a resource-rational representation problem. Specifically, we propose that people decompose tasks in a manner that facilitates efficient use of limited cognitive resources given the structure of the environment and their own planning algorithms. Using this model, we replicate several existing findings. Our account provides a normative explanation for how people identify subtasks as well as a framework for studying how people reason, plan, and act using resource-rational representations.
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