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Found 4 papers, 1 papers with code
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints
This study presents a benchmark for evaluating action-constrained reinforcement learning (RL) algorithms.
H2 Performance Analysis and Synthesis for Discrete-Time Linear Systems with Dynamics Determined by an i.i.d. Process
This paper is concerned with H2 control of discrete-time linear systems with dynamics determined by an independent and identically distributed (i. i. d.)
Stochastic Aperiodic Control of Networked Systems with i.i.d. Time-Varying Communication Delays
The delays are theoretically not required to be bounded even when the plant is unstable in the deterministic sense.
Contraction Analysis of Discrete-time Stochastic Systems
In this paper, we develop a novel contraction framework for stability analysis of discrete-time nonlinear systems with parameters following stochastic processes.
