4 citations · 10 across the 3 of their papers we have counts for
6 papers
Insurance pricing on price comparison websites via reinforcement learning
Tanut Treetanthiploet, Yufei Zhang, Lukasz Szpruch +4
The emergence of price comparison websites (PCWs) has presented insurers with unique challenges in formulating effective pricing strategies. Operating on PCWs requires insurers to…
Optimal scheduling of entropy regulariser for continuous-time linear-quadratic reinforcement learning
Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang
This work uses the entropy-regularised relaxed stochastic control perspective as a principled framework for designing reinforcement learning (RL) algorithms. Herein agent interacts…
Exploration-exploitation trade-off for continuous-time episodic reinforcement learning with linear-convex models
Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang
We develop a probabilistic framework for analysing model-based reinforcement learning in the episodic setting. We then apply it to study finite-time horizon stochastic control prob…
Generalised correlated batched bandits via the ARC algorithm with application to dynamic pricing
Samuel Cohen, Tanut Treetanthiploet
The Asymptotic Randomised Control (ARC) algorithm provides a rigorous approximation to the optimal strategy for a wide class of Bayesian bandits, while retaining low computational…
Asymptotic Randomised Control with applications to bandits
Samuel N. Cohen, Tanut Treetanthiploet
We consider a general multi-armed bandit problem with correlated (and simple contextual and restless) elements, as a relaxed control problem. By introducing an entropy regularisati…
Gittins' theorem under uncertainty
Samuel N. Cohen, Tanut Treetanthiploet
We study dynamic allocation problems for discrete time multi-armed bandits under uncertainty, based on the the theory of nonlinear expectations. We show that, under strong independ…