Deep neural networks have achieved impressive successes in fields ranging from object
recognition to complex games such as Go,. Navigation, however, remains a substantial
challenge for artificial agents, with deep neural networks trained by reinforcement learning,–
failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid
cells in the entorhinal cortex. Grid cells are thought to provide a multi-scale periodic
representation that functions as a metric for coding space, and is critical for integrating self …

Efficient navigation is a fundamental component of mammalian behaviour but remains
challenging for artificial agents. Mammalian spatial behaviour is underpinned by grid cells in
the entorhinal cortex, providing a multi-scale periodic representation that functions as a
metric for coding space. Grid cells are viewed as critical for integrating self-motion (path
integration) and planning direct trajectories to goals (vector-based navigation). We report, for
the first time, that brain-like grid representations can emerge as the product of optimizing a …