MobEvolve is an agentic self-evolving heuristic framework that generates interpretable human mobility trajectories and outperforms deep generative and LLM-based methods on Singapore and Montreal benchmarks.
arXiv preprint arXiv:2407.18932 , year=
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GenWorld supplies a data-grounded synthetic urban environment, structured agent interface, and offline LLM policy compilation to enable scalable city-scale LLM-agent simulations, shown via three cases in Higashihiroshima with census and mobile-data checks.
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MobEvolve: An Agentic Self-Evolving Heuristic System for Interpretable Human Mobility Generation
MobEvolve is an agentic self-evolving heuristic framework that generates interpretable human mobility trajectories and outperforms deep generative and LLM-based methods on Singapore and Montreal benchmarks.