5 papers · 1 filter
Mirror Descent for Stochastic Control Problems with Measure-valued Controls
Bekzhan Kerimkulov, David Å iÅ¡ka, Åukasz Szpruch +1
This paper studies the convergence of the mirror descent algorithm for finite horizon stochastic control problems with measure-valued control processes. The control objective invol…
Logarithmic regret in the ergodic Avellaneda-Stoikov market making model
Jialun Cao, David Šiška, Lukasz Szpruch +1
We analyse the regret arising from learning the price sensitivity parameter of liquidity takers in the ergodic version of the Avellaneda-Stoikov market making model. We show t…
A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces
Bekzhan Kerimkulov, James-Michael Leahy, David Siska +2
We study the global convergence of a Fisher-Rao policy gradient flow for infinite-horizon entropy-regularised Markov decision processes with Polish state and action space. The flow…
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…
Linear convergence of proximal descent schemes on the Wasserstein space
Razvan-Andrei Lascu, Mateusz B. Majka, David Šiška +1
We investigate proximal descent methods, inspired by the minimizing movement scheme introduced by Jordan, Kinderlehrer and Otto, for optimizing entropy-regularized functionals on t…