Lessons from Contextual Bandit Learning in a Customer Support BotDownload PDF

May 05, 2019 (edited Jun 03, 2019)ICML 2019 Workshop RL4RealLife SubmissionReaders: Everyone
  • Keywords: reinforcement learning, contextual bandits, off-policy RL
  • Abstract: In this work, we describe practical lessons we have learned from successfully using contextual bandits (CBs) to improve key business metrics of the Microsoft Virtual Agent for customer support. While our current use cases focus on single step reinforcement learning (RL) and mostly in the domain of natural language processing and information retrieval we believe many of our findings are generally applicable. Through this article, we highlight certain issues that RL practitioners may encounter in similar types of applications as well as offer practical solutions to these challenges.
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