This makes it crucial to align autonomous AI systems with their users' intentions. Precisely specifying which behaviours are or are not desirable is challenging, however. One approach to this specification problem is to learn an approximation of the true reward function (Ng et al., 2000;

In Figure 9 we provide bias and MSE analysis of different algorithms on the domains that exhibit passive non-stationarity.

FCL T results in the Markov chain setting, an alternative condition that is more applicable for SA problems is established.

Human-AI shared control allows human to interact and collaborate with autonomous agents to accomplish control tasks in complex environments.