4 citations · 4 across the 3 of their papers we have counts for
1 paper · 1 filter
Jack Harmer, Linus Gisslén, Jorge del Val +5
In this work we describe a novel deep reinforcement learning architecture that allows multiple actions to be selected at every time-step in an efficient manner. Multi-action polici…