COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goal
Yi Cheng, Wenge Liu, Jian Wang, Chak Tou Leong, Yi Ouyang, Wenjie Li,, Xian Wu, Yefeng Zheng

TL;DR
COOPER is a novel framework that coordinates specialized agents to collaboratively achieve complex dialogue goals like persuasion and emotional support, addressing the challenges of strategic reasoning and goal measurement.
Contribution
It introduces a divide-and-conquer approach by coordinating multiple specialized agents, improving performance on complex dialogue tasks.
Findings
Outperforms baseline methods in persuasion dialogues
Effective in emotional support dialogue scenarios
Demonstrates the benefits of specialized agent collaboration
Abstract
In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond traditional service-focused dialogue systems. Apart from the requirement for much more sophisticated strategic reasoning and communication skills, a significant challenge of these tasks lies in the difficulty of objectively measuring the achievement of their goals in a quantifiable way, making it difficult for existing research to directly optimize the dialogue procedure towards them. In our work, we emphasize the multifaceted nature of complex dialogue goals and argue that it is more feasible to accomplish them by comprehensively considering and jointly promoting their different aspects. To this end, we propose a novel dialogue framework, Cooper, which coordinates multiple specialized agents, each dedicated to a…
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Code & Models
Videos
Taxonomy
TopicsSpeech and dialogue systems · Topic Modeling · Multi-Agent Systems and Negotiation
MethodsSparse Evolutionary Training
