Reinforcement Learning for Spoken Dialogue Systems : Comparing Strengths and Weaknesses for Practical Deployment

@inproceedings{Paek2006ReinforcementLF,
  title={Reinforcement Learning for Spoken Dialogue Systems : Comparing Strengths and Weaknesses for Practical Deployment},
  author={Tim Paek},
  year={2006}
}
In a spoken dialogue system, the function of a dialogue manager is to select actions based on observed events and inferred beliefs. To formalize and optimize the action selection process, researchers have turned to reinforcement learning methods which represent the dynamics of a spoken dialogue as a fully or partially observable Markov Decision Process. Once represented as such, optimal policies prescribing what actions the system should take in order to maximize a reward function can be… CONTINUE READING
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