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Theory-Informed Generative Agents for Human Mobility Modeling

2026-02-25

Abstract excerpt

<title>Abstract</title> <p>Human mobility follows robust population-level regularities, yet individual behavior remains highly heterogeneous and context-dependent. The advances of generative agents (large language model (LLM)–driven, persona-conditioned computational agents) offer a promising approach to modeling rich, individualized behavior, but they often lack theoretical grounding and do not readily scale to...

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Literature Corpus work
eda36651-d4d6-54d4-b4a4-38956bfd7c57
DOI
10.21203/rs.3.rs-8902418/v1
Open publication

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