Many collective human activities, including violence, have been shown to exhibit universal patterns. The size distributions of casualties both in whole wars from 1816 to 1980 and terrorist attacks have separately been shown to follow approximate power-law distributions. However, the possibility of universal patterns ranging across wars in the size distribution or timing of within-conflict events has barely been explored. Here we show that the sizes and timing of violent events within different insurgent conflicts exhibit remarkable similarities. We propose a unified model of human insurgency that reproduces these commonalities, and explains conflict-specific variations quantitatively in terms of underlying rules of engagement. Our model treats each insurgent population as an ecology of dynamically evolving, self-organized groups following common decision-making processes. Our model is consistent with several recent hypotheses about modern insurgency, is robust to many generalizations, and establishes a quantitative connection between human insurgency, global terrorism and ecology. Its similarity to financial market models provides a surprising link between violent and non-violent forms of human behaviour.
Cluster sampling has recently been used to estimate the mortality in various conflicts around the world. The Burnham et al. study on Iraq employs a new variant of this cluster sampling methodology. The stated methodology of Burnham et al. is to (1) select a random main street, (2) choose a random cross street to this main street, and (3) select a random household on the cross street to start the process. The authors show that this new variant of the cluster sampling methodology can introduce an unexpected, yet substantial, bias into the resulting estimates, as such streets are a natural habitat for patrols, convoys, police stations, roadblocks, cafes, and street-markets. This bias comes about because the residents of households on cross-streets to the main streets are more likely to be exposed to violence than those living further away. Here, the authors develop a mathematical model to gauge the size of the bias and use the existing evidence to propose values for the parameters that underlie the model. The research suggests that the Burnham et al. study of conflict mortality in Iraq may represent a substantial overestimate of mortality. Indeed, the recently published Iraq Family Health Survey covered virtually the same time period as the Burnham et al. study, used census-based sampling techniques, and produced a central estimate for violent deaths that was one fourth of the Burnham et al. estimate. The authors provide a sensitivity analysis to help readers to tune their own judgements on the extent of this bias by varying the parameter values. Future progress on this subject would benefit from the release of high-resolution data by the authors of the Burnham et al. study.
We examine, numerically and analytically, the effect of network connections within a frustrated system where heterogeneous, adaptive nodes ("agents") compete for limited global resources. We uncover a rich spectrum of non-ergodic dynamics. Whether the network connections turn out to be beneficial or detrimental is found to depend quite dramatically on the global resource level.
We analyse the effects of agents' decisions on the creation of congestion on a centralised network with ring-and-hub topology. We show that there are two classes of agents each displaying a distinct set of behaviours. The dynamics of the system are driven by an interplay between the formation of, and transition between, unique stable states that arise as the network is varied. We show how the flow of objects across the network can be understood in terms of the ordering and allocation of strategies. Our results show that the existence of congestion in a network is a dynamic process that is as much dependent on the agents' decisions as it is on the structure of the network itself.
We study Complex Adaptive Systems in which information is shared locally within a heterogeneous population of adaptive nodes ('agents') competing for a limited global resource. The emerging collective behaviour is found to depend strongly on the level of available resource, the connectivity between agents and the accuracy of information transmission.
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