Refuel: Exploring sparse features in deep reinforcement learning for fast disease diagnosis

YS Peng, KF Tang, HT Lin… - Advances in neural …, 2018 - proceedings.neurips.cc
This paper proposes REFUEL, a reinforcement learning method with two techniques:{\em
reward shaping} and {\em feature rebuilding}, to improve the performance of online symptom …

[PDF][PDF] REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis

YS Peng, KF Tang, HT Lin, EY Chang - scholar.archive.org
This paper proposes REFUEL, a reinforcement learning method with two techniques: reward
shaping and feature rebuilding, to improve the performance of online symptom checking for …

[PDF][PDF] REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis

YS Peng, KF Tang, HT Lin, EY Chang - papers.neurips.cc
This paper proposes REFUEL, a reinforcement learning method with two techniques: reward
shaping and feature rebuilding, to improve the performance of online symptom checking for …

REFUEL: exploring sparse features in deep reinforcement learning for fast disease diagnosis

YS Peng, KF Tang, HT Lin, EY Chang - Proceedings of the 32nd …, 2018 - dl.acm.org
This paper proposes REFUEL, a reinforcement learning method with two techniques: reward
shaping and feature rebuilding, to improve the performance of online symptom checking for …

[PDF][PDF] REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis

YS Peng, KF Tang, HT Lin, EY Chang - csie.ntu.edu.tw
This paper proposes REFUEL, a reinforcement learning method with two techniques: reward
shaping and feature rebuilding, to improve the performance of online symptom checking for …

REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis

YS Peng, KF Tang, HT Lin… - Advances in Neural …, 2018 - proceedings.neurips.cc
This paper proposes REFUEL, a reinforcement learning method with two techniques:{\em
reward shaping} and {\em feature rebuilding}, to improve the performance of online symptom …