IL, or behavioral cloning, is the process by which observations and actions are captured from a human, or perhaps another AI, and used as input into training an agent. The agent essentially becomes guided by the human and learns by their actions and observations. A set of learning observations can be received by real-time play (online) or be extracted from saved games (offline). This provides the ability to capture play from multiple agents and train them in tandem or individually. IL provides the ability to train or, in effect, program agents for tasks you may find impossible to train for using regular RL, and because of this, it will likely become a key RL technique that we use for most tasks in the near future.
It is hard to gauge the value something gives you until you see what things are like without it. With that in mind, we will first start by...