Search Results for author:
Found 3 papers, 0 papers with code
Abstracting Linear Stochastic Systems via Knowledge Filtering
In this paper, we propose a new model reduction technique for linear stochastic systems that builds upon knowledge filtering and utilizes optimal Kalman filtering techniques.
Policy Evaluation in Distributional LQR
Distributional reinforcement learning (DRL) enhances the understanding of the effects of the randomness in the environment by letting agents learn the distribution of a random return, rather than its expected value as in standard RL.
Online Control Synthesis for Uncertain Systems under Signal Temporal Logic Specifications
It is shown that when the STL formula is robustly satisfiable and the initial state of the system belongs to the initial root node of the tTLT, it is guaranteed that the trajectory generated by the control synthesis algorithm satisfies the STL formula.
