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Intell. Syst. Technol."],"published-print":{"date-parts":[[2024,4,30]]},"abstract":"<jats:p>\n            Daily activity data recording individuals\u2019 various activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, and policymaking. Though with high value, its accessibility is limited due to high collection costs and potential privacy issues. Therefore, simulating human activities to produce massive high-quality data is of great importance. However, existing solutions, including rule-based methods with simplified behavior assumptions and data-driven methods directly fitting real-world data, both cannot fully qualify for matching reality. In this article, motivated by the classic psychological theory, Maslow\u2019s need theory describing human motivation, we propose a knowledge-driven simulation framework based on generative adversarial imitation learning. Our core idea is to model the evolution of human needs as the underlying mechanism that drives activity generation in the simulation model. Specifically, a hierarchical model structure that disentangles different need levels and the use of neural stochastic differential equations successfully capture the piecewise-continuous characteristics of need dynamics. Extensive experiments demonstrate that our framework outperforms the state-of-the-art baselines regarding data fidelity and utility. We also present the insightful interpretability of the need modeling. Moreover, privacy preservation evaluations validate that the generated data does not leak individual privacy. The code is available at\n            <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"url\" xlink:href=\"https:\/\/github.com\/tsinghua-fib-lab\/Activity-Simulation-SAND\">https:\/\/github.com\/tsinghua-fib-lab\/Activity-Simulation-SAND<\/jats:ext-link>\n            .\n          <\/jats:p>","DOI":"10.1145\/3637493","type":"journal-article","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T11:42:31Z","timestamp":1702554151000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Generating Daily Activities with Need Dynamics"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1701-2588","authenticated-orcid":false,"given":"Yuan","family":"Yuan","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7985-6263","authenticated-orcid":false,"given":"Jingtao","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6382-0861","authenticated-orcid":false,"given":"Huandong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0419-5514","authenticated-orcid":false,"given":"Depeng","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,2,22]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"308","volume-title":"CCS","author":"Abadi Martin","year":"2016","unstructured":"Martin Abadi, Andy Chu, Ian Goodfellow, H. 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