A Novel Approach for Modeling Complex Deep Futures

TL;DR

This paper introduces a new modeling approach for complex deep futures by partitioning the problem into actor and domain layers, integrating data-driven parameters, and applying advanced computational techniques for scenario analysis.

Contribution

It proposes a novel layered framework for modeling complex systems, combining uncertainty analysis and computational methods to explore future states.

Findings

Effective partitioning of complex systems into two layers.

Integration of data sources for parameter assessment.

Use of advanced computational techniques for scenario analysis.

Abstract

Many large-scale, complex systems consist of interactions between humans, human-made systems and the environment. The approach developed in this paper is to partition the problem space into two fundamental layers and identify, parameterize and model the main dimensions of each layer and interactions across and in between layers. One layer is the key actors or major organization or human decision makers who influence the state of the world. The other layer includes the domains or fields of knowledge relevant to the problem being addressed. These domains include elements such as the physical earth and its atmosphere, world demography, world economy, level of globalization, and politics. Key parameters for each of the actor types and domains will be extracted and assessed using existing data sources. Novel systems, uncertainty modeling and analysis techniques are combined with advanced computational technologies to determine a spectrum of likely future system states and conduct ifthen scenario analyses.