Robot Learning

Subgoal

A subgoal is an intermediate target state or condition that decomposes a long-horizon task into shorter, independently achievable segments, such as "grasp the handle" within "open the drawer and retrieve the tool". Hierarchical methods have a high-level process — a learned high-level policy, a symbolic planner, or a language model — propose subgoals that a low-level goal-conditioned policy then reaches; subgoals may be expressed as states, images, language, or latent vectors.

Why it matters for physical AI

Credit assignment across thousands of timesteps defeats flat policies; subgoal decomposition is the main lever for extending today's short-horizon skills to multi-stage real-world tasks.