When one agent interacts with a multi-agent environment, it is challenging to
deal with various opponents unseen before. Modeling the behaviors, goals, or
beliefs of opponents could help the agent adjust its policy to adapt to
different opponents. In addition, it is also important to c
本研究提出了一种 for identifying the priorities of the opponent in multi-issue negotiation from partial dialogues，通过关键词识别和数据适应的方法，对话模型在零散输入数据的情况下，能准确预测对手的所重视的议题顺序。