Insurance pricing on price comparison websites via reinforcement learning

no code implementations • 14 Aug 2023 • Tanut Treetanthiploet, Yufei Zhang, Lukasz Szpruch, Isaac Bowers-Barnard, Henrietta Ridley, James Hickey, Chris Pearce

The emergence of price comparison websites (PCWs) has presented insurers with unique challenges in formulating effective pricing strategies.

reinforcement-learning Reinforcement Learning (RL)

Optimal scheduling of entropy regulariser for continuous-time linear-quadratic reinforcement learning

no code implementations • 8 Aug 2022 • 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.

reinforcement-learning Reinforcement Learning (RL) +1

Exploration-exploitation trade-off for continuous-time episodic reinforcement learning with linear-convex models

no code implementations • 19 Dec 2021 • Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang

We develop a probabilistic framework for analysing model-based reinforcement learning in the episodic setting.

Model-based Reinforcement Learning Reinforcement Learning (RL)

Generalised correlated batched bandits via the ARC algorithm with application to dynamic pricing

no code implementations • 8 Feb 2021 • 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 complexity.

Asymptotic Randomised Control with applications to bandits

no code implementations • 14 Oct 2020 • 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.

Multi-Armed Bandits