Offline training is where a recorded gameplay file is generated from a player or agent playing a game or performing a task, and is then fed back as training observations to help an agent learn later on. While online learning certainly is more fun, and in some ways more applicable to the Tennis scene or other multiplayer games, it is less practical. After all, you generally need to play an agent in real time for several hours before an agent will become good. Likewise, in online training scenarios, you are typically limited to single agent training, whereas in offline training a demo playback can be fed to multiple agents for better overall learning. This also allows us to perform interesting training scenarios, similar to AlphaStar training, where we can teach an agent so that it can teach other agents.
Offline training
We will learn more about multi-agent gameplay in Chapter...
