In plain words: Everyday routines like "wait for the green light, then go" can be written as short code-like scripts; a language model drafts possible scripts, and probability rules pick which one best fits a person's few observed actions. From just a handful of observations, this predicted behavior in game and household simulations up to 50% better than standard pattern-copying and language-model approaches.
Abstract
Accurate prediction of human behavior is essential for robust and safe human-AI collaboration. However, existing approaches for modeling people are often data-hungry and brittle because they either make unrealistic assumptions about rationality or are too computationally demanding to adapt rapidly. Our key insight is that many everyday social interactions may follow predictable patterns; efficient "scripts" that minimize cognitive load for actors and observers, e.g., "wait for the green light, then go." We propose modeling these routines as behavioral programs instantiated in computer code rather than policies conditioned on beliefs and desires. We introduce ROTE, a novel algorithm that leverages both large language models (LLMs) for synthesizing a hypothesis space of behavioral programs, and probabilistic inference for reasoning about uncertainty over that space. We test ROTE in a suite of gridworld tasks and a large-scale embodied household simulator. ROTE predicts human and AI behaviors from sparse observations, outperforming competitive baselines -- including behavior cloning and LLM-based methods -- by as much as 50% in terms of in-sample accuracy and out-of-sample generalization. By treating action understanding as a program synthesis problem, ROTE opens a path for AI systems to efficiently and effectively predict human behavior in the real-world.
Kunal Jha, Aydan Yuenan Huang, Eric Ye, Natasha Jaques, Max Kleiman-Weiner
arXiv:2510.01272 · cs.AI, cs.LG · submitted Sep 29, 2025
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Aren't there already materials (made for people with autism) that catalog these scripts and make them explicit?
Edit: e.g. https://suelarkey.com.au/promoting-social-understanding-soci...