Producing flexible behaviours in simulated environments DeepMind

For some AI problems, such as playing Atari or Go, the goal is easy to define - it's winning. But how do you describe the process for performing a backflip? The difficulty of accurately describing a complex behaviour is a common problem when teaching motor skills to an artificial system. In this work we explore how sophisticated behaviors can emerge from scratch from the body interacting with the environment using only simple high-level objectives, such as moving forward without falling. Specifically, we trained agents with a variety of simulated bodies to make progress across diverse terrains, which require jumping, turning and crouching.