The Skeleton in the Cognitive Map

Experts seem to find routes in a complex environment by finding a connection from the starting place to a subset of major paths—the “skeleton”—then moving within the skeleton to the neighborhood of the destination, making a final connection to the destination. We present a computational hypothesis to account for the skeleton as an emergent phenomenon, arising from the interaction of three factors. (1) The topological map is represented as a bipartite graph of places and paths, where a path is an extended one-dimensional description of an ordered set of places. (2) Travel through the environment allows the traveler to incrementally accumulate topological relationships, including the relation of a place to a path serving as a dividing boundary separating two regions. (3) A bounding path is often a natural subgoal during way-finding search, meaning that paths rich in boundary relations are likely to appear in routes, which means they are likely to acquire more boundary relations. This positive-feedback loop leads to an oligarchy of paths rich in boundary relations. We propose computational and empirical tests for this hypothesis. Expert way-finders in a complex large-scale environment use a “skeleton” of important paths and places to guide their problem-solving (Lynch 1960, Pailhous 1969, Chase 1982). How is this skeleton represented? How is it acquired? And how does it help in way-finding? In this note, I describe a preliminary computational hypothesis to explain the phenomenon of the skeleton, based on the concepts in the Spatial Semantic Hierarchy (Kuipers 2000} (which extends the TOUR Model (Kuipers 1978, Kuipers 1982)). I also describe a set of computational and cognitive tests that could be applied to this hypothesis. This note proposes a hypothesis and raises questions for investigation, rather than providing definitive