{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T06:36:52Z","timestamp":1770273412647,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>In recent years, computational improvements have allowed for more nuanced, data-driven and geographically explicit agent-based simulations. Yet, simulations have struggled to adequately represent the attributes that motivate and drive agents\u2019 actions. Existing population synthesis frameworks usually generate agent profiles limited to socio-demographic attributes. In this paper, we introduce a novel population synthesis framework that integrates a motivational layer into the traditional individual and house-hold socio-demographic layers. Our research extends the profile of agents in synthetic populations to incorporate data on values, ideologies, opinions and vital priorities, all of which play a key role in motivating agents\u2019 behaviour. This motivational layer paves the way for developing data-driven decision-making mechanisms in future agent-based simulations. Our methodology combines microdata and macrodata within different Bayesian network structures or models. This method allows to generate synthetic populations that integrate motivational information while preserving the inherent socio-demographic distributions of the real population.<\/jats:p>","DOI":"10.3233\/faia251255","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:56:03Z","timestamp":1761126963000},"source":"Crossref","is-referenced-by-count":1,"title":["Population Synthesis with Motivational Attributes: A Path Towards Cultural Variation in Agent-Based Models"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5336-8570","authenticated-orcid":false,"given":"Alba","family":"Aguilera","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Institute (IIIA-CSIC), Barcelona"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1666-8421","authenticated-orcid":false,"given":"Miquel","family":"Albert\u00ed","sequence":"additional","affiliation":[{"name":"Universitat de Barcelona, Barcelona"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2766-3475","authenticated-orcid":false,"given":"Nardine","family":"Osman","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute (IIIA-CSIC), Barcelona"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1320-3873","authenticated-orcid":false,"given":"Georgina","family":"Curto","sequence":"additional","affiliation":[{"name":"United Nations University Institute in Macau, Macau SAR, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251255","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:56:04Z","timestamp":1761126964000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251255"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251255","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}