The agility and flexibility of a monkey swinging through the trees or a football player dodging opponents and scoring a goal can be breathtaking. Mastering this kind of sophisticated motor control is a hallmark of physical intelligence, and is a crucial part of AI research.

True motor intelligence requires learning how to control and coordinate a flexible body to solve tasks in a range of complex environments. Existing attempts to control physically simulated humanoid bodies come from diverse fields, including computer animation and biomechanics. A trend has been to use hand-crafted objectives, sometimes with motion capture data, to produce specific behaviors. However, this may require considerable engineering effort, and can result in restricted behaviours or behaviours that may be difficult to repurpose for new tasks.



In three new papers, we seek ways to produce flexible and natural behaviours that can be reused and adapted to solve tasks.