Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings

3rd Conversational AI Workshop at 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) 2019 Jorge A. MendezAlborz GeramifardMohammad GhavamzadehBing Liu

Learning task-oriented dialog policies via reinforcement learning typically requireslarge amounts of interaction with users, which in practice renders such methodsunusable for real-world applications. In order to reduce the data requirements, wepropose to leverage data from across different dialog domains, thereby reducingthe amount of data required from each given domain... (read more)

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