REVIEW 1 cited by
Convexification for a Coefficient Inverse Problem of Mean Field Games
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
Signed reviews
read the original abstract
The globally convergent convexification numerical method is constructed for a Coefficient Inverse Problem for the Mean Field Games System. A coefficient characterizing the global interaction term is recovered from the single measurement data. In particular, a new Carleman estimate for the Volterra integral operator is proven, and it stronger than the previously known one. Numerical results demonstrate accurate reconstructions from noisy data.
Forward citations
Cited by 1 Pith paper
-
Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems
GPPI-AS offers a mesh-free, closed-form policy iteration solver for HJB and mean field game forward and inverse problems, with Schwarz acceleration cutting iterations roughly in half.
Discussion (0). Continue with ORCID to comment.