REVIEW
Adaptive dynamic programming-based algorithm for infinite-horizon linear quadratic stochastic optimal control problems
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Adaptive dynamic programming-based algorithm for infinite-horizon linear quadratic stochastic optimal control problems
read the original abstract
This paper investigates an infinite-horizon linear quadratic stochastic (LQS) optimal control problem for a class of continuous-time stochastic systems. By employing the technique of adaptive dynamic programming (ADP), we propose a novel model-free policy iteration (PI) algorithm. Without needing all information of the system coefficient matrices, the proposed PI algorithm iterates by using the data of the input and system state collected on a fixed time interval. Finally, a numerical example is presented to demonstrate the feasibility of the obtained algorithm.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.