Distributed computing in practice: the Condor experience: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Data farming in Singapore: a brief history
Proceedings of the 40th Conference on Winter Simulation
Automated red teaming: an objective-based data farming approach for red teaming
Proceedings of the 40th Conference on Winter Simulation
Enhancing automated red teaming with evolvable simulation
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Research advances in automated red teaming
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Maritime counter-piracy study using agent-based simulations
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Application of multi-objective bee colony optimization algorithm to automated red teaming
Winter Simulation Conference
Evolutionary design of experiments using the MapReduce framework
Proceedings of the 2011 Summer Computer Simulation Conference
Effective crowd control through adaptive evolution of agent-based simulation models
Proceedings of the Winter Simulation Conference
Evolvable simulations applied to automated red teaming: a preliminary study
Proceedings of the Winter Simulation Conference
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In this paper, we describe Automated Red Teaming (ART), a concept that uses Evolutionary Algorithm (EA), Parallel Computing and Simulation to complement the manual Red Teaming effort to uncover system vulnerabilities or to find exploitable gaps in military operational concepts. The overall goal is to reduce surprises, improve and ensure the robustness of the Blue ops concepts. The design of key components and techniques that are required to develop an ART framework are described and discussed. An experiment with a military scenario in Urban Operations (UO) was conducted and the results analyzed to demonstrate the capability of the ART framework. Results showed that Red Force survivability can be improved by 27% just by modifying behavioral parameters alone. These findings could be used by Blue Force to refine their tactics and strategy thereby ensuring robustness of plans and higher mission success.