Multi-scale decision making: challenges in engineering and environmental systems

Many systems analyses involve a variety of decisions defined over different temporal, physical, and organizational scales. Scale issues may introduce dependencies and influences between decisions that are difficult to anticipate or untangle with standard methods from optimization, decision theory, and risk management. These issues are made all the more important by the rapid proliferation of technology (sensors, communications, and computing) that supports the collection and processing of new types of data on unprecedented scales (‘‘big data’’ decision making). Multi-scale decision problems arise in a variety of domains, including environmental management, manufacturing and production, service systems, and finance. Multi-scale decision making is closely related to the topic of distributed decision making. There exists a large literature on distributed models for optimization and planning, with problems often classified in terms of the hierarchies that exist between decision makers (see, e.g., Deng and Papadimitriou 1999; Schneeweiss 2010). The artificial intelligence community also has considered distributed problems, with emphasis on machine learning problems in taxonomies defined in terms of paradigms for information exchange among agents (see, e.g., Doran et al. 1997; Weiss 1999; Brafman and Tennenholtz 2011). Recently, Wernz and Deshmukh (2010, 2012) have proposed a unified mathematical framework for multi-scale problems which defines decision hierarchies and information exchange in a game theoretic model. In keeping with the theme of the journal, this special issue of Environment Systems & Decisions explores multiscale decision making from a decidedly more applied perspective. In practice, the context for decision making is where many of the true difficulties lie. Multi-scale problems often cut across organizations and stakeholder groups, and the texture of these environments may defy the kind of smooth information exchange and hierarchical characterizations so easily postulated in mathematical models. As an example of how multi-scale decision making can be driven by issues that arise from systems context, consider the growing importance of security in systems design and operation. A decision problem that might have been properly modeled as one of coordinating the actions of distributed elements within an organization must now be recast to account for the presence of an intelligent adversary. This in turn creates linkages in the decision problem among many new stakeholders, including the adversary itself. Several of the principal challenges in multi-scale decision making are outlined below. In each case, references are made to the most relevant papers in the special issue.