Fig. 3: Learned transition graphs form a reusable schema.

A CSCG trained on one room (a) and partial observations in a second, previously unseen room with identical hidden layout, utilizes the learned structure of the room to rapidly find both the shortest path to the origin (b) and navigate around obstacles (c). d Visualization of message propagation during planning and replanning. Messages propagate outward from the starting clone, and clones that receive the message are indicated in green color. Lighter shades indicate messages that are later in time. The first plan is unaware of the obstacle, and the agent discovers the obstacle only when the action sequence is executed and a planned action fails (red arrow). This initiates a replanning from the new location, and the new plan routes around the obstacle. e–g The transition matrix (graph) learned in one room can be used as a reusable structure to quickly learn a new room with the same layout but different observations. Learning is faster when CSCG transition graph is used as a schema to learn the new room (g) compared to learning from scratch (f).