Complexity theory is one of the most controversial areas of current scientific research. Developing out of chaos theory, complexity suggests that there are hidden tendencies in nature to select ordered states, even when statistically they are vastly outnumbered by chaotic possibilities: that there is a deep natural impulse towards order, counteracting the degenerative tendencies of the Second Law of Thermodynamics. Like chaos, complexity is a multidisciplinary area of research and those involved include physicists, economists and biologists. This is a study of complexity.

At Home in the Universe: The Search for the Laws of Self-Organization and Complexity

 Four appendices summarize valuable resources available for the reader: Appendix A contains printed and recorded resources, Appendix B suggests web-related resources, Appendix C discusses GP software tools, including Discipulus, the GP software developed by the authors, and Appendix D mentions events most closely related to the field of genetic programming. URLs can be found online at http://mkp.com/GPIntro.

Genetic Programming: An Introduction

Prior research developed a cellular automaton model, that was calib- rated by using historical digital maps of urban areas and can be used to predict the future extent of an urban area. The model has now been applied to two rapidly growing, but remarkably diA erent urban areas: the San Francisco Bay region in California and the Washington/Baltimore corridor in the Eastern United States. This paper presents the calibration and prediction results for both regions, reviews their data requirements, compares the diA erences in the initial con® gura- tions and control parameters for the model in the two settings, and discusses the role of GIS in the applications. The model has generated some long term predic- tions that appear useful for urban planning and are consistent with results from other models and observations of growth. Although the GIS was only loosely coupled with the model, the model's provision of future urban patterns as data layers for GIS description and analysis is an important outcome of this type of calculation.

/pdf/loose-coupling-a-cellular-automaton-model-and-gis-long-term-4582h6lvif.pdf

Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore.

Energy systems models are important methods used to generate a range of insight and analysis on the supply and demand of energy. Developed over the second half of the twentieth century, they are now seeing increased relevance in the face of stringent climate policy, energy security and economic development concerns, and increasing challenges due to the changing nature of the twenty-first century energy system. In this paper, we look particularly at models relevant to national and international energy policy, grouping them into four categories: energy systems optimization models, energy systems simulation models, power systems and electricity market models, and qualitative and mixed-methods scenarios. We examine four challenges they face and the efforts being taken to address them: (1) resolving time and space, (2) balancing uncertainty and transparency, (3) addressing the growing complexity of the energy system, and (4) integrating human behavior and social risks and opportunities. In discussing these challenges, we present possible avenues for future research and make recommendations to ensure the continued relevance for energy systems models as important sources of information for policy-making.

https://www.pfenninger.org/publications-pdf/Pfenninger%20et%20al_2014_Energy%20systems%20modeling%20for%20twenty-first%20century%20energy%20challenges.pdf

Energy systems modeling for twenty-first century energy challenges

The impact of supply chain complexity on manufacturing plant performance

Books-Received - Complexity - the Emerging Science at the Edge of Order and Chaos

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Books-Received - Complexity - the Emerging Science at the Edge of Order and Chaos