The author argues that correcting the residual error in policy gradient estimation can improve sample efficiency in reinforcement learning. They propose a log density gradient method to address this issue.
Residual error correction in policy gradient estimation can improve sample efficiency in reinforcement learning.
Log density gradient corrects for residual error in policy gradient estimation, improving sample efficiency in reinforcement learning.
Die Log Density Policy Gradient Methode korrigiert Fehler in der Gradientenschätzung und verbessert die Effizienz von Verstärkungslernverfahren.