SwarmAgentic：通过群体智能实现全自动智能体系统生成
SwarmAgentic: Towards Fully Automated Agentic System Generation via Swarm Intelligence
AI总结：
针对现有智能体系统生成缺乏自主性的问题，提出SwarmAgentic框架，从零构建并联合优化智能体功能与协作，在六个任务上超越基线，显著提升性能。
摘要：
大型语言模型的快速发展推动了智能体系统在决策、协调和任务执行方面的进步。然而，现有的智能体系统生成框架缺乏完全自主性，缺少从零开始的智能体生成、自我优化的智能体功能以及协作能力，限制了其适应性和可扩展性。我们提出了SwarmAgentic，一个用于全自动智能体系统生成的框架，该框架从零开始构建智能体系统，并通过语言驱动的探索，将智能体功能和协作作为相互依赖的组件进行联合优化。为了实现对系统级结构的高效搜索，SwarmAgentic维护一个候选系统种群，并受粒子群优化（PSO）启发，通过反馈引导的更新来进化这些系统。我们在六个涉及高层规划、系统级协调和创造性推理的真实世界、开放性和探索性任务上评估了我们的方法。仅给定任务描述和目标函数，SwarmAgentic在所有基线上均表现优异，在TravelPlanner基准上相对于ADAS实现了+261.8%的相对改进，突显了在结构无约束任务中全自动化的有效性。该框架标志着向可扩展和自主的智能体系统设计迈出的重要一步，将群体智能与全自动系统多智能体生成相结合。我们的代码已在https://yaoz720.github.io/SwarmAgentic/公开发布。
英文摘要：
The rapid progress of Large Language Models has advanced agentic systems in decision-making, coordination, and task execution. Yet, existing agentic system generation frameworks lack full autonomy, missing from-scratch agent generation, self-optimizing agent functionality, and collaboration, limiting adaptability and scalability. We propose SwarmAgentic, a framework for fully automated agentic system generation that constructs agentic systems from scratch and jointly optimizes agent functionality and collaboration as interdependent components through language-driven exploration. To enable efficient search over system-level structures, SwarmAgentic maintains a population of candidate systems and evolves them via feedback-guided updates, drawing inspiration from Particle Swarm Optimization (PSO). We evaluate our method on six real-world, open-ended, and exploratory tasks involving high-level planning, system-level coordination, and creative reasoning. Given only a task description and an objective function, SwarmAgentic outperforms all baselines, achieving a +261.8% relative improvement over ADAS on the TravelPlanner benchmark, highlighting the effectiveness of full automation in structurally unconstrained tasks. This framework marks a significant step toward scalable and autonomous agentic system design, bridging swarm intelligence with fully automated system multi-agent generation. Our code is publicly released at https://yaoz720.github.io/SwarmAgentic/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
