3 ms·

I don't find this particularly impressive for DeepMind, mostly because it seems like a ballistics/physics problem rather than a machine learning problem. Edit:

• smegma2 1y ago
  The paper addresses this. Part of the goal was to let the world model be learned rather than modeled explicitly by the programmer. > To date, the Omron Forpheus robot [73], [62] has the closest capabilities to the agent presented in this work, demonstrating sustained rallies on a variety of stroke styles with skilled human players. A key point of difference is that our agent learns the control policies and perception system, whereas the Forpheus agent uses a model-based approach. More specifically, Forpheus leverages rebound and aerodynamics models in order to identify the optimal configuration of the robot so as to return the ball to a target position. The Omron system represents a highly engineered system that cannot easily be customized to new players, environments, or paddles. > While there have been many demonstrations of robots playing table tennis against human players in the past, we believe this research is one of the first human-robot interaction studies to be conducted with full competitive matches against such a wide range of player skill levels.