MANTA: Multi-Agent Network Topology Adaptation for Self-Evolving Multi-Agent Systems

Published
Source
arXiv
Paper number
785
Field
AI / General
arXiv ID
2607.28527

Key points

  • We propose structural self-improvement, which changes the communication topology in real time while solving the task instead of fixing it before execution.
  • It reuses structures learned from past experience before a task starts and partially revises them when problems arise during execution.
  • Across five benchmarks, it averages 74.0 points, 5.8 points higher than the previous best.
  • Rather than simply increasing the number of agents, it improves structure by rewiring connections or adding verification steps.
  • Meta-level operations, meaning structure planning and revision, account for only about 12% of total token usage, so it is efficient.
  • It also has the lowest token usage among multi-agent systems.

Paper links

External research summaries. These are not HDATF publications or measured product results.

Read original (opens in a new tab)