The Brain Predicts Reward Like an AI, Says New DeepMind Research

The idea of reinforcement learning--or learning based on reward--has been around for so long it's easy to forget we don't really know how it works. If DeepMind's new bombshell paper in Nature is any indication, a common approach in AI, one that's led to humanity's defeat in the game of Go against machines, may have the answer. We all subconsciously learn complex behaviors in response to positive and negative feedback, but how that works in the brain remains a century-long mystery. By examining a powerful variant of reinforcement learning, dubbed distributional reinforcement learning, that outperforms original methods, the team suggests that the brain may simultaneously represent multiple predicted futures in parallel. Each future is assigned a different probability, or chance of actually occurring, based on reward.