Symbiotic Adaptive Multisimulation: An Autonomic Simulation Framework For Real-time Decision Support Under Uncertainty

摘要

Inspired by the compound arthropod eye, Symbiotic Adaptive Multisimulation (SAMS) introduces an autonomic decision support capability for systems in shifting, ill-defined, uncertain environments. Rather than rely on a single authoritative model, SAMS explores an ensemble of plausible models, which are individually flawed but collectively provide more insight than would be possible otherwise. A case study based on a UAV team search and attack model is presented to illustrate the potential of SAMS. Results demonstrate the capability of SAMS to produce a large degree of exploratory behavior, followed by increased exploitative search behavior as the physical system unfolds.