Chat-Like Conversational System Based on Selection of Reply Generating Module with Reinforcement Learning

Abstract

This paper presents a chat-like conversational system, and that generates a reply by selecting an appropriate reply generating module. Such modules consist in selecting a sentence from an article of Web news, retrieving a definition sentence in Wikipedia, question-answering, and so on. A dialogue strategy corresponds to which reply generating module should be chosen according to a user input and the dialogue history, and is learned in the MDP framework. User evaluations showed that our system could learn an appropriate dialogue strategy, and perform natural dialogues.