Strategic positioning in tactical scenario planning
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Computational scenario-based capability planning
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Research advances in automated red teaming
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Evolutionary design of experiments using the MapReduce framework
Proceedings of the 2011 Summer Computer Simulation Conference
VCELL: a 3D real-time visual simulation in support of combat
Proceedings of the 2011 Summer Computer Simulation Conference
ABSNEC: an agent-based system for network enabled capabilities/operations
SCSC '09 Proceedings of the 2009 Summer Computer Simulation Conference
Evolvable simulations applied to automated red teaming: a preliminary study
Proceedings of the Winter Simulation Conference
Analysis of key installation protection using computerized red teaming
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
An agent-based model to simulate and analyse behaviour under noisy and deceptive information
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
The causes for no causation: A computational perspective
Information-Knowledge-Systems Management - Complex Socio-Technical Systems --Understanding and Influencing Causality of Change
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Red teaming is the process of studying a problem by anticipating adversary behaviors. When done in simulations, the behavior space is divided into two groups; one controlled by the red team which represents the set of adversary behaviors or bad guys, while the other is controlled by the blue team which represents the set of defenders or good guys. Through red teaming, analysts can learn about the future by forward prediction of scenarios. More recently, defense has been looking at evolutionary computation methods in red teaming. The fitness function in these systems is highly stochastic, where a single configuration can result in multiple different outcomes. Operational, tactical and strategic decisions can be made based on the findings of the evolutionary method in use. Therefore, there is an urgent need for understanding the nature of these problems and the role of the stochastic fitness to gain insight into the possible performance of different methods. This paper presents a first attempt at characterizing the search space difficulties in red teaming to shed light on the expected performance of the evolutionary method in stochastic environments.