← Search

Changxi Zhu

2 accepted papers

2022

A Versatile Adaptive Curriculum Learning Framework for Task-oriented Dialogue Policy Learning

NAACL 2022findings

Training a deep reinforcement learning-based dialogue policy with brute-force random sampling is costly. A new training paradigm was proposed to improve learning performance and efficiency by combining curriculum learning. However, attempts in the field of dialogue policy are very limited due to the…

Cited by 4SourcePDFScholar
2021

Efficient Dialogue Complementary Policy Learning via Deep Q-network Policy and Episodic Memory Policy

EMNLP 2021main

Deep reinforcement learning has shown great potential in training dialogue policies. However, its favorable performance comes at the cost of many rounds of interaction. Most of the existing dialogue policy methods rely on a single learning system, while the human brain has two specialized learning a…

Cited by 13SourcePDFScholar