Web: http://arxiv.org/abs/2209.08429

Sept. 20, 2022, 1:14 a.m. | Mohammad Kachuee, Sungjin Lee

cs.CL updates on arXiv.org arxiv.org

Recently, self-learning methods based on user satisfaction metrics and
contextual bandits have shown promising results to enable consistent
improvements in conversational AI systems. However, directly targeting such
metrics by off-policy bandit learning objectives often increases the risk of
making abrupt policy changes that break the current user experience. In this
study, we introduce a scalable framework for supporting fine-grained
exploration targets for individual domains via user-defined constraints. For
example, we may want to ensure fewer policy deviations in business-critical
domains …

ai systems arxiv conversational conversational ai optimization policy self-learning systems

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