Luchen Li

Luchen Li
Imperial College London | Imperial · Department of Computing

Doctor of Philosophy

About

4
Publications
389
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Introduction
Luchen Li currently works at the Department of Computing, Imperial College London. Luchen does research in Artificial Intelligence, Electrical Engineering and Computer Engineering. Their current project is 'Brain & Behaviour Lab - Imperial College London (Faisal Lab)'.
Education
August 2015 - December 2016
Carnegie Mellon University
Field of study
  • Electrical and Computer Engineering
September 2011 - June 2015
Beihang University (BUAA)
Field of study
  • Electronics and Information Engineering

Publications

Publications (4)
Preprint
Full-text available
Distributional Reinforcement Learning (RL) maintains the entire probability distribution of the reward-to-go, i.e. the return, providing more learning signals that account for the uncertainty associated with policy performance, which may be beneficial for trading off exploration and exploitation and policy learning in general. Previous works in dis...
Preprint
Full-text available
Our aim is to establish a framework where reinforcement learning (RL) of optimizing interventions retrospectively allows us a regulatory compliant pathway to prospective clinical testing of the learned policies in a clinical deployment. We focus on infections in intensive care units which are one of the major causes of death and difficult to treat...
Preprint
Full-text available
Health-related data is noisy and stochastic in implying the true physiological states of patients, limiting information contained in single-moment observations for sequential clinical decision making. We model patient-clinician interactions as partially observable Markov decision processes (POMDPs) and optimize sequential treatment based on belief...
Preprint
Full-text available
Off-policy reinforcement learning enables near-optimal policy from suboptimal experience, thereby provisions opportunity for artificial intelligence applications in healthcare. Previous works have mainly framed patient-clinician interactions as Markov decision processes, while true physiological states are not necessarily fully observable from clin...

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