SwarmAgentic

Towards Fully Automated Agentic System Generation via Swarm Intelligence

SwarmAgentic is 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.

Key Features

🛠️ Autonomous, from scratch

Builds complete multi-agent systems directly from task descriptions and an objective function, jointly optimizing both functionality and collaboration without predefined templates or seed workflows.

🐝 Language-driven PSO

Reformulates particle swarm optimization into interpretable text–symbol updates over agent roles and coordination structures, enabling language-mediated exploration of the system design space.

🔁 Failure-aware refinement

Leverages LLM-guided flaw detection and failure memory to prevent repeated suboptimal adjustments and focus updates on meaningful improvements.

🚀 Robust generalization

Demonstrates strong performance and transferability across diverse real-world, open-ended tasks requiring high-level planning, multi-agent coordination, and complex reasoning.

Results

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.

References