Resource-rational Task Decomposition to Minimize Planning Costs

TL;DR

This paper introduces a resource-rational model for task decomposition, explaining how humans break down tasks to minimize planning costs by efficiently using limited cognitive resources, aligning with observed behaviors.

Contribution

It formalizes task decomposition as a resource-rational problem, providing a normative framework for understanding human planning and task segmentation.

Findings

Replicates several existing findings on task decomposition.

Provides a normative explanation for subtask identification.

Offers a framework for studying human reasoning and planning.

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.