Modeling natural resources exploitation in low-information environments

Abstract

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.