Fuzzy Cognitive Maps of Public Support for Insurgency and Terrorism
نویسندگان
چکیده
Feedback fuzzy cognitive maps (FCMs) can model the complex structure of public support for insurgency and terrorism (PSOT). FCMs are fuzzy signed directed graphs that model degrees of causality in interwoven webs of feedback causality and policy variables. Their nonlinear dynamics permit forward-chaining inference from input causes and policy options to output effects. We show how a concept node causally affects downstream nodes through a weighted product of the intervening causal edge strengths. FCMs allow users to add detailed dynamics and feedback links directly to the causal model. Users can also fuse or combine FCMs from multiple experts by weighting and adding the underlying FCM fuzzy edge matrices. The combined FCM tends to better represent domain knowledge as the expert sample size increases if the expert sample approximates a random sample. Statistical or machine-learning algorithms can use numerical sample data to learn and tune a FCM’s causal edges. A differential Hebbian learning law can approximate a PSOT FCM’s directed edges of partial causality using time-series training data. The PSOT FCM adapts to the computational factor-tree PSOT model that Davis and O’Mahony based on prior social science research and case studies. Simulation experiments compare the factor-tree PSOT model with the adapted FCM models.
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I like war, has an enduring nature and a changing character. It remains a strategy entailing violence used by the weak and desperate against a power system.1 Often (but not always), this pits a nonstate or proto-state organization against a state. Out of weakness, the organization using a strategy of insurgency attempts to shift the focus of conflict away from domains where the state or other p...
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