Difference between revisions of "Imitation Learning (IL)"
| Line 10: | Line 10: | ||
* [[Learning Techniques]] | * [[Learning Techniques]] | ||
** [[Reinforcement Learning]] | ** [[Reinforcement Learning]] | ||
| − | * [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]] | + | ** [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]] |
* [[Inside Out - Curious Optimistic Reasoning]] | * [[Inside Out - Curious Optimistic Reasoning]] | ||
* [[Generative Adversarial Network (GAN)]] | * [[Generative Adversarial Network (GAN)]] | ||
Revision as of 10:18, 23 February 2020
YouTube search... ...Google search
The ongoing explosion of spatiotemporal tracking data has now made it possible to analyze and model fine-grained behaviors in a wide range of domains. For instance, tracking data is now being collected for every NBA basketball game with players, referees, and the ball tracked at 25 Hz, along with annotated game events such as passes, shots, and fouls. Other settings include laboratory animals, people in public spaces, professionals in settings such as operating rooms, actors speaking and performing, digital avatars in virtual environments, and even the behavior of other computational systems.
