cs.MA · 2026-08-22 · No. 92

Multiagent Systems, 2026-08-22.

2 new papers in cs.MA. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Reward-Guided Autoregressive Graph Generation for Efficient Multi-Agent Communication Topology Design

    Poomphob Suwannapichat, Boonyarit Changaival, Caesar Wu, Pascal Bouvry

    cs.MA · cs.CL · cs.LG

    LLM-based Multi-Agent Systems (MAS) achieve strong performance on complex reasoning tasks by coordinating multiple agents, but at the cost of substantial token consumption. Recent work on automatic topology design, ARG-Designer, has reframed this problem as autoregressive graph generation. However, its training objective provides no explicit incentive for the model to generate sparse and efficient topologies. We address this limitation by...

    arxiv.org/abs/2608.20099 · PDF

  2. 02

    Distilling Aggregate Mobility Statistics into a Language Model Policy for Post-Event Crowd Simulation

    Tatsuya Amano, Hirozumi Yamaguchi

    cs.MA · cs.AI

    Pedestrian simulators need a behaviour rule for every agent, but privacy usually limits the data for setting one to aggregate statistics, namely zone-level device counts and origin-to-destination (OD) flows, with no individual trajectories. Such aggregates under-determine individual behaviour, because many different sets of decisions reproduce the same counts. We fine-tune a language model crowd agent so that the simulated population matches...

    arxiv.org/abs/2608.19778 · PDF

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