Symbiotic adaptive multisimulation: An autonomic simulation framework for real-time decision support under uncertainty

Authors:
Bradley Mitchell;Levent Yilmaz
Affiliations:
Auburn University, Auburn, AL;Auburn University, Auburn, AL
Venue:
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Year:
2009

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Abstract

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.