AI-Driven, Physics-Based Character Animation

With adversarial reinforcement learning, physically simulated characters can be developed that automatically synthesize lifelike and responsive behaviors. A character is first trained to perform complex motor skills by imitating human motion data. Once the character has acquired a rich repertoire of skills, it can reuse those skills to perform new tasks in a natural, lifelike way. This model then allows you to generate motions for new scenarios, without tedious manual animation or new motion data from real actors.