000136187 001__ 136187 000136187 005__ 20250908131433.0 000136187 0247_ $$2doi$$a10.1088/2632-072X/ad5cb9 000136187 0248_ $$2sideral$$a139164 000136187 037__ $$aART-2024-139164 000136187 041__ $$aeng 000136187 100__ $$aMuñoz-Álvarez, Silvia 000136187 245__ $$aModeling natural resources exploitation in low-information environments 000136187 260__ $$c2024 000136187 5060_ $$aAccess copy available to the general public$$fUnrestricted 000136187 5203_ $$aThe sustainable exploitation of natural resources constitutes a real-world problem of interest for many fields. In this work, we study those situations in which the exploiting agents have information about the state of the resource and their own benefits and costs but not about the behavior or performance of the rest of the agents. Cognitive Hierarchy Theory provides a framework for those low-information scenarios by focusing on the assumptions that agents make about other individuals’ behavior. Motivated by this theory, we introduce a theoretical agent-based model in which agents exhibit varying degrees of rationalization when exploiting the resource, and this resource’s evolution is driven by a differential equation that mirrors the dynamics of real-world resource growth. Our results show that, although most regimes imply depletion, higher benefits and sustainability are obtained when agents assume overexploitation by the rest and try to compensate for it. Furthermore, many exploiting agents and a long-term perspective also involve a better resource state, reaching the optimal exploitation level when all these factors come together. 000136187 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-115800GB-I00 000136187 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000136187 592__ $$a0.641$$b2024 000136187 593__ $$aArtificial Intelligence$$c2024$$dQ2 000136187 593__ $$aInformation Systems$$c2024$$dQ2 000136187 593__ $$aComputer Science Applications$$c2024$$dQ2 000136187 593__ $$aComputer Networks and Communications$$c2024$$dQ2 000136187 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000136187 700__ $$0(orcid)0000-0002-9769-8796$$aGracia-Lázaro, Carlos 000136187 700__ $$0(orcid)0000-0002-0895-1893$$aMoreno, Yamir$$uUniversidad de Zaragoza 000136187 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDpto. Física Teórica$$cÁrea Física Teórica 000136187 773__ $$g5, 3 (2024), 035002$$tJournal of Physics: Complexity$$x2632-072X 000136187 8564_ $$s620600$$uhttps://zaguan.unizar.es/record/136187/files/texto_completo.pdf$$yVersión publicada 000136187 8564_ $$s608128$$uhttps://zaguan.unizar.es/record/136187/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000136187 909CO $$ooai:zaguan.unizar.es:136187$$particulos$$pdriver 000136187 951__ $$a2025-09-08-12:56:42 000136187 980__ $$aARTICLE