This paper describes NJFun, a real-time spoken dialogue system that provides users with information about things to do in New Jersey. NJFun automatically optimizes its dialogue strategy over time, by using a methodology for applying reinforcement learning to a working dialogue system with human users.
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Litman et al. (2000) studied this question.
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