基于深度学习技术的谈判机器人开发

Mei-Yao Chang, Jan-Pan Hwang
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引用次数: 4

摘要

本研究结合人工智能技术RNN/LSTM开发了一个对话系统,主要应用于谈判课程的议价单元。将聊天机器人应用于学生议价情景演练的对话中,探讨了该对话系统在课程中应用的可行性。这个两小时的课程有48名来自不同学院和系的大学二年级学生参加。结果表明,大多数学生对即时通讯进行对话练习持积极态度,并感到有趣。该小组以对话机器人为目标,学生更喜欢课程。对于真人小组,学生认为这对学习更有帮助,他们对议价谈判的结果有更高的满意度。
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Developing Chatbot with Deep Learning Techniques for Negotiation Course
this research combines the artificial intelligence technique RNN/LSTM to develop a dialogue system, which mainly used in the bargaining unit of a negotiation course. The chatbot was applied in the dialogue of student drills in bargaining situations and investigates the feasibility of the dialogue system used in the course. The two-hour course has 48 second-year university students with different colleges and departments. The results show that most students have a positive view of instant messaging conducts dialogue exercises, and feel interesting. The groups targeting dialogue robots, students prefer courses. For groups with real people, students think it is more helpful for learning, and they have higher satisfaction with the results of bargaining negotiations.
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