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Hi, I implemented NFQ a while ago (#897) and have since noticed some things that could be improved. Changes are summarized below:
In addition to increased uniformity, this also consumes much less memory on the gpu compared to the previous version, which needed to duplicate all input data |action space| times to loop over all actions. The main drawback is that it is less faithful to the original implementation [1].
[1] Riedmiller, M. (2005). Neural Fitted Q Iteration – First Experiences with a Data Efficient Neural Reinforcement Learning Method. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds) Machine Learning: ECML 2005. ECML 2005. Lecture Notes in Computer Science(), vol 3720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564096_32