Generative World Modelling for Humanoids: 1X World Model Challenge Technical Report
Technical report detailing our method that won the 1X World Model Challenge 2025.
Riccardo Mereu
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1 min readTechnical report detailing our method that won the 1X World Model Challenge 2025.
Introduction World models equip agents (e.g., humanoid robots) with internal simulators of their environments. By “imagining” the consequences of their actions, agents can plan, …
In reinforcement learning (RL), world models serve as internal simulators, enabling agents to predict environment dynamics and future outcomes in order to make informed decisions. …