Navigating with grid-like representations in artificial agents
Most animals, including humans, are able to flexibly navigate the world they live in – exploring new areas, returning quickly to remembered places, and taking shortcuts. Indeed, these abilities feel so easy and natural that it is not immediately obvious how complex the underlying processes really are. In contrast, spatial navigation remains a substantial challenge for artificial agents whose abilities are far outstripped by those of mammals.
In 2005, a potentially crucial part of the neural circuitry underlying spatial behaviour was revealed by an astonishing discovery: neurons that fire in a strikingly regular hexagonal pattern as animals explore their environment. This lattice of points is believed to facilitate spatial navigation, similarly to the gridlines on a map. In addition to equipping animals with an internal coordinate system, these neurons - known as grid cells - have recently been hypothesised to support vector-based navigation. That is: enabling the brain to calculate the distance and direction to a desired destination, "as the crow flies," allowing animals to make direct journeys between different places even if that exact route had not been followed before.
The group that first discovered grid cells was jointly awarded the 2014 Nobel Prize in Physiology or Medicine for shedding light on how cognitive representations of space might work. But after more than 10 years of theorising since their discovery, the computational functions of grid cells -- and whether they support vector-based navigation -- has remained largely a mystery.
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