Topic: systematic generalization

Cognitive maps associate complex, high-dimensional stimuli, such as visual percepts, with abstract latent variables, such as spatial locations. It has been argued that animals use these abstract spatial features to navigate and infer novel shortcuts in their environments. Employing information theory, we present a simple computational account of how such abstract spatial representations may emerge from interactions with high-dimensional stimuli: We show that learning world models in which the dynamics are parsimonious and apply (approximately) independently of the state in an abstract state sp