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.
arXiv preprint arXiv:2506.23306 , year=
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AgentMob is a training-free LLM-driven agent that formulates mobility prediction as adaptive evidence-controlled decision making and outperforms other training-free LLM methods on three datasets.
SenseWalk is an LLM-powered agent-based simulation system for semantic trajectories that combines LLMs with the social force model, supported by a user interface, quantitative evaluation, and a user study with 12 participants.
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SenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned Environments
SenseWalk is an LLM-powered agent-based simulation system for semantic trajectories that combines LLMs with the social force model, supported by a user interface, quantitative evaluation, and a user study with 12 participants.