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math.OC2025
Mirror descent for constrained stochastic control problems
Deven Sethi, David Šiška
Mirror descent is a well established tool for solving convex optimization problems with convex constraints. This article introduces continuous-time mirror descent dynamics for appr…
math.OC2024★ 2 cited
Entropy annealing for policy mirror descent in continuous time and space
Deven Sethi, David Šiška, Yufei Zhang
Entropy regularization has been widely used in policy optimization algorithms to enhance exploration and the robustness of the optimal control; however it also introduces an additi…
math.OC2022
The Modified MSA, a Gradient Flow and Convergence
Deven Sethi, David Šiška
The modified Method of Successive Approximations (MSA) is an iterative scheme for approximating solutions to stochastic control problems in continuous time based on Pontryagin Opti…