arXiv AI
Oct 31

Goal-Aware Dynamic Multi-Agent Collaboration for Long-Horizon Tasks

The paper introduces Goal-Aware Dynamic Multi-Agent Collaboration (GAD), a framework that assigns distinct duties to separate agents with individualized contexts to tackle long-horizon tasks. It employs a growing execution graph to structure subtasks and their dependencies, ensuring each agent retains the original instruction, task goal, and acceptance conditions. GAD dynamically adapts collaboration and information sharing, using verification and recovery checks to monitor subtask results and overall task completion, providing feedback for repair when checks fail.

By Xu Shen, Lingyong Yan, Shuaiqiang Wang, Jianmin Wu, Zhikai Chen, Jiliang Tang, Jie Ren