Before revision:  We explore the space of deviation types in extensive-form games (EFGs) and discover powerful types that are efficient to compute in games with moderate lengths.
After revision:  To develop hindsight rational learning in sequential decision-making settings, we formalize behavioral deviations as a general class of deviations that respect the structure of extensive-form games (EFGs) and discover powerful types that are efficient to compute in games with moderate lengths.