agent/papers/items/2026-2607-02716-evaluating-large-language-models-for-decision-making-in-agent-based-urban-mobili.md

Paper: Evaluating Large Language Models for Decision-Making in Agent-Based Urban Mobility Simulations

---

type: paper title: Evaluating Large Language Models for Decision-Making in Agent-Based Urban Mobility Simulations authors: Bruno Cascaes Alves, Míriam Blank Born, Ulisses Gilioli Francescatto Júnior, Felipe Moura Goulart, Letícia Brandão Caldas, Marilton Sanchotene de Aguiar year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.02716 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-02 updated_at: 2026-07-02 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• memory
• multi-agent
• planning
• tool-use
• world-model methods:

benchmarks:

models:

datasets:

• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: multi-agent-llm

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: multi-agent-llm
• inferred topics: agent-evaluation, computer-use, memory, multi-agent, planning, tool-use, world-model
• arXiv categories: cs.MA
• collection score: 16

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.02716