Conclusion

The Loglet Lab software package provides a means of running the models as described in this paper by making the mechanisms behind the model transparent to the user. Ease of use allows us to envision several scenarios in a manner of minutes, as we can quickly run these models several times with different parameterizations. Combining this with a diverse range of visualizations, Loglet Lab offers a rich analysis of data sets which exhibit complex growth.

Yet underlying the complexity of these models are parameters with concrete and, more importantly, informative interpretations. The emphasis of loglet analysis becomes not building or running the model, but interpreting it.

Acknowledgements: We thank Arnulf Gruebler, John Helm, Cesare Marchetti, Nebojsa Nakicenovic, Paul Waggoner, and Iddo Wernick.