  This document is a guide to the implementation of true online emphatic
TD($\lambda$), a model-free temporal-difference algorithm for learning to make
long-term predictions which combines the emphasis idea (Sutton, Mahmood & White
2015) and the true-online idea (van Seijen & Sutton 2014). The setting used
here includes linear function approximation, the possibility of off-policy
training, and all the generality of general value functions, as well as the
emphasis algorithm's notion of "interest".
