  In domains such as homeland security, cybersecurity and competitive
marketing, it is frequently the case that analysts need to forecast adversarial
actions that impact the problem of interest. Standard structured expert
judgement elicitation techniques may fall short as they do not explicitly take
into account intentionality. We present a decomposition technique based on
adversarial risk analysis followed by a behavioral recomposition using discrete
choice models that facilitate such elicitation process and illustrate its
performance through behavioral experiments.
