We introduce the ActiveVOO framework for active knowledge acquisition to identify, quantify, and prioritize task-relevant information for open-world embodied planning.

A novel intrinsic motivation method based on world-model memory mismatch enables embodied agents to exhibit robust autonomous behaviors that closely match whole-brain neural data from zebrafish.