End-to-End Reinforcement Learning of Dialogue Agents for Information Access
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强化学习在任务驱动型对话系统中的应用。这篇文章提出一个KB-InfoBot，它是一个通过交互询问特征的方式为用户从知识库（KB）中提供实体的对话智能体，KB-InfoBot的成分都是用强化学习以end-to-end的方式训练。
任务驱动的对话系统需要与外部数据库交互，这种智能体在交互式查询中有应用。
实体模型是可微的，这意味这系统可以只用来自用户的强化学习信号实现端到端训练。
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- 【翻译】End-to-End Reinforcement Learning of Dialogue Agents for Information Access
- End-to-End Reinforcement Learning of Dialogue Agents for Information Access
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