A DQN chatbot that selects among 100 clustered reply types and is rewarded for picking true human responses learns on training dialogues but generalizes poorly to unseen dialogues.
Attention, intentions, and the structure of discourse,
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Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards
A DQN chatbot that selects among 100 clustered reply types and is rewarded for picking true human responses learns on training dialogues but generalizes poorly to unseen dialogues.