We investigate non-collaborative dialogue agents that must engage in tailored strategic planning for diverse users to secure a favorable agreement. This poses challenges for existing dialogue agents due to two main reasons: their inability to integrate user-specific characteristics into their strategic planning and their training paradigm's failure to produce strategic planners that can generalize to diverse users. To address these challenges, we propose TRIP to enhance the capability in tailored strategic planning, incorporating a user-aware strategic planning module and a population-based training paradigm. Through experiments on benchmark non-collaborative dialogue tasks, we demonstrate the effectiveness of TRIP in catering to diverse users.

提出了TRIP用于增强定制战略规划的能力，通过引入用户感知的战略规划模块和基于人口统计的训练范式，解决了现有对话代理面临的两大挑战：无法将用户特定特征纳入战略规划以及无法对多样化用户进行泛化训练。通过在标准的非合作对话任务上进行实验，证明了TRIP在迎合多样化用户方面的有效性。

优势在于差异！通过量身定制的策略规划实现有效的非合作性对话