Dec 17, 2022 · These findings show that managing the temporal resolution can provably improve policy evaluation efficiency in LQR systems with finite data.
Feb 1, 2023 · TL;DR: By analyzing Monte-Carlo value estimation for LQR systems we uncover a fundamental trade-off between approximation and statistical error ...
With finite data, a higher temporal resolution means that more data is collected within fewer episodes. This inevitably leads to the question on how to ...
Our results uncover a fundamental trade-off for choosing an optimal step-size that leads to a minimal MSE. One-Dimensional Langevin Process To simplify the ...
May 30, 2024 · These findings show that managing the temporal resolution can provably improve policy evaluation efficiency in LQR systems with finite data.
Our results uncover a fundamental trade-off for choosing an optimal step-size that leads to a minimal MSE. One-Dimensional Langevin Process To simplify the ...
Dec 17, 2022 · These findings show how adapting the temporal resolution can provably improve value estimation quality in LQR systems from finite data.
Duration: 1:42
Posted: Dec 7, 2023
Posted: Dec 7, 2023
Model-based reinforcement learning with value-targeted regression ... Managing temporal resolution in continuous value estimation: A fundamental trade-off.
... Managing temporal resolution in continuous value estimation: A fundamental trade-off. In Advances in Neural Information Processing Systems (NeurIPS-23) ...