DFBT forecasts the missing delayed states in one direct transformer pass instead of recursively, reducing compounding belief errors and improving delayed-RL performance.
1−L P δ 1−L P ϵP # , then it is obvious that we have Itrue ∆ (xt) +LVϵdirect | {z } |Idirect(xt)| ≤ Itrue ∆ (xt) +LV E δ∼d∆(·)
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Directly Forecasting Belief for Reinforcement Learning with Delays
DFBT forecasts the missing delayed states in one direct transformer pass instead of recursively, reducing compounding belief errors and improving delayed-RL performance.