Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration

@article{Shi2021RefineAI,
  title={Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration},
  author={Weiyan Shi and Yu Li and Saurav Sahay and Zhou Yu},
  journal={ArXiv},
  year={2021},
  volume={abs/2012.15375}
}
Persuasion dialogue systems reflect the machine’s ability to make strategic moves beyond verbal communication, and therefore differen-tiate themselves from task-oriented or open-domain dialogue systems and have their own unique values. However, the repetition and inconsistency problems still persist in dialogue response generation and could substantially impact user experience and impede the persuasion outcome. Besides, although reinforcement learning (RL) approaches have achieved big success in… 

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