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Abstract
It is proposed that a cognitive map encoding the relationships between entities in
the world supports flexible behavior, but the majority of the neural evidence for
such a system comes from studies of spatial navigation. Recent work describing neuronal
parallels between spatial and non-spatial behaviors has rekindled the notion of a
systematic organization of knowledge across multiple domains. We review experimental
evidence and theoretical frameworks that point to principles unifying these apparently
disparate functions. These principles describe how to learn and use abstract, generalizable
knowledge and suggest that map-like representations observed in a spatial context
may be an instance of general coding mechanisms capable of organizing knowledge of
all kinds. We highlight how artificial agents endowed with such principles exhibit
flexible behavior and learn map-like representations observed in the brain. Finally,
we speculate on how these principles may offer insight into the extreme generalizations,
abstractions, and inferences that characterize human cognition.