An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email

An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email (2000)

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by Marilyn A. Walker

Venue:	JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
Citations:	47 - 7 self

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@ARTICLE{Walker00anapplication,
    author = {Marilyn A. Walker},
    title = { An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email},
    journal = {JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH},
    year = {2000},
    volume = {12},
    pages = {387--416}
}

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Abstract

This paper describes a novel method by which a spoken dialogue system can learn to choose an optimal dialogue strategy from its experience interacting with human users. The method is

Citations

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