We are interested in the problem of how an agent organizes its sensorimotor experiences in order to create a spatial representation. Our approach to solve this problem is the Spatial Semantic Hierarchy (SSH), where multiple levels of spatial representation coexists. At the SSH topological level, space is represented by places and connectivity relation among them. Places are arranged into streets so that the topological representation looks like the street network of a city. Grouping places into regions allows an agent to reason efficiently about its spatial knowledge. Different types of regions can be defined as the agent travels in the environment. Using the language of Causal Theories, we give a formal account of how an agent establishes boundary region relations while navigating its environment.
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