Toward nature-inspired computing
Communications of the ACM
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Decentralized energy systems (DESs), which are open and dynamically evolving systems, play advantageous roles in facilitating the utilization of sustainable resources (SRs) in remote rural areas. In this paper, we present a self-organizing mechanism by focusing on the nature-inspired behaviors of autonomous agents for improving the transport efficiency of SRs, which is a major obstacle for their extensive utilization. Three nature-inspired behavioral rules are proposed to provide feasible solutions from the viewpoint of problem-solving, and most importantly, to understand the relationships between the local interactions and decision-making of autonomous agents and the transport efficiency of a DES from the viewpoint of policy-making. Simulation results on both static and dynamic environments show that our mechanism can approach to optimal transport efficiency by tuning a control parameter. Moreover, benefiting from the nonlinear aggregation of cost information among self-organizing agents, it is computationally scalable for energy transportation in large-scale DESs. Practically, our mechanism may help gain a deep insight into energy policy issues in DESs such as transportation network planning from a self-organizing systems perspective.