# Exploring the hierarchical structure of human plans via program generation

**Authors:** Carlos G. Correa, Sophia Sanborn, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths  
**arXiv:** [2311.18644](https://arxiv.org/abs/2311.18644)  
**Date:** 2023-11-30  
**Summary page:** https://www.summarizepaper.com/fr/paper/2311.18644v1/

## Abstract

Human behavior is inherently hierarchical, resulting from the decomposition of a task into subtasks or an abstract action into concrete actions. However, behavior is typically measured as a sequence of actions, which makes it difficult to infer its hierarchical structure. In this paper, we explore how people form hierarchically-structured plans, using an experimental paradigm that makes hierarchical representations observable: participants create programs that produce sequences of actions in a language with explicit hierarchical structure. This task lets us test two well-established principles of human behavior: utility maximization (i.e. using fewer actions) and minimum description length (MDL; i.e. having a shorter program). We find that humans are sensitive to both metrics, but that both accounts fail to predict a qualitative feature of human-created programs, namely that people prefer programs with reuse over and above the predictions of MDL. We formalize this preference for reuse by extending the MDL account into a generative model over programs, modeling hierarchy choice as the induction of a grammar over actions. Our account can explain the preference for reuse and provides the best prediction of human behavior, going beyond simple accounts of compressibility to highlight a principle that guides hierarchical planning.