136187 20260219090928.0 doi 10.1088/2632-072X/ad5cb9 sideral 139164 ART-2024-139164 eng Muñoz-Álvarez, Silvia Modeling natural resources exploitation in low-information environments 2024 Access copy available to the general public Unrestricted The 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. info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL info:eu-repo/grantAgreement/ES/MICINN/PID2020-115800GB-I00 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 1.9 2024 0.641 2024 Artificial Intelligence 2024 Q2 Information Systems 2024 Q2 Computer Science Applications 2024 Q2 Computer Networks and Communications 2024 Q2 4.7 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Gracia-Lázaro, Carlos (orcid)0000-0002-9769-8796 Moreno, Yamir Universidad de Zaragoza (orcid)0000-0002-0895-1893 2004 405 Universidad de Zaragoza Dpto. Física Teórica Área Física Teórica 5, 3 (2024), 035002 Journal of Physics: Complexity 2632-072X 620600 http://zaguan.unizar.es/record/136187/files/texto_completo.pdf Versión publicada 608128 http://zaguan.unizar.es/record/136187/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:136187 articulos driver 2026-02-19-09:00:04 ARTICLE