arXiv AI
Sep 4

Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

The paper introduces Imagine-then-Plan (ITP), a framework that lets agents learn by interacting with a learned world model to generate multi-step imagined trajectories. ITP features an adaptive lookahead mechanism that balances ultimate goals with task progress, producing richer signals about future outcomes. Experiments on various benchmarks show that ITP outperforms existing baselines, and analyses suggest the adaptive lookahead improves reasoning for complex tasks.

By Youwei Liu, Jian Wang, Hanlin Wang, Beichen Guo, Wenjie Li