Optimal Stationary Value of Drift-Dominated Controlled Diffusion Processes: Computational Challenges and Effective Algorithms.

Aaron Palmer (Dept. of Mathematics, Cornell University)

Efficient numerical methods are well-known for deterministic optimal
control problems and for diffusion-dominated controlled drift-diffusion
problems. However, neither class of methods is efficient when
the diffusion term is degenerate or the drift term is dominant.
In this talk we explore adaptations of value and policy iteration
algorithms along with Gauss-Seidel relaxation to compute approximate
optimal value, and hence the optimal feedback control, in the region
between deterministic and non-degenerate stochastic problems.

(Joint work with A. Vladimirsky.)