2025 ACL ACL 2025

ACT: Knowledgeable Agents to Design and Perform Complex Tasks

Abstract

AbstractLarge language models enhance collaborative task execution in multi-agent systems. Current studies break complex task into manageable tasks, but agents lack understanding of the overall task and how others approach their tasks, hindering synergy and integration.We propose a method called knowledgeable Agents to design and perform Complex Tasks (ACT), where: (1) Agents independently manage their knowledge and tasks while collaboratively design the complex task into a more comprehensible form. In parallel, each agent also acquires knowledge of others, defined as a structured description of how other agents approach their tasks based on the agent’s own task resolution. (2) Each agent updates its knowledge and refines its task through interactions with others. By referencing structured knowledge, they effectively integrate their tasks to collaboratively solve the complex task.Three evaluations including creative writing and tool utilization, show that ACT accurately outperforms existing methods in solving complex tasks.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🧭 Keyword Pioneer — knowledge management
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics