Emotional support conversation (ESC) aims to provide emotional support (ES)
to improve one's mental state. Existing works stay at fitting grounded
responses and responding strategies (e.g., question), which ignore the effect
on ES and lack explicit goals to guide emotional positive transition. To this
end, we introduce a new paradigm to formalize multi-turn ESC as a process of
positive emotion elicitation. Addressing this task requires finely adjusting
the elicitation intensity in ES as the conversation progresses while
maintaining conversational goals like coherence. In this paper, we propose
Supporter, a mixture-of-expert-based reinforcement learning model, and well
design ES and dialogue coherence rewards to guide policy's learning for
responding. Experiments verify the superiority of Supporter in achieving
positive emotion elicitation during responding while maintaining conversational
goals including coherence.

本研究提出了一种新的情感支持对话范式 —— 正向情感引导，通过基于专家的混合增强学习模型，精细的情感调节以及对话连贯性的奖励设计，达到实现情感支持和维护对话连贯性的双重目标。实验结果证明了该模型在提高积极情感引导能力方面的优越性，同时也保持了对话的连贯性。