Meeting Description: This Working Group deals with two interdependent questions – both related to our understanding of complex systems. The first is to do with the ‘Hierarchical Organization’ of a system. The main question here is: Can those same info-metrics tools (that also include the tools of information theory and the maximum entropy principle) provide insight into the properties of complex systems for which discrete hierarchical scales are not readily resolvable? In more general terms, the basic issue here is to study whether there is a distinction (and if so, what it is) between complex systems that are organized into discrete hierarchical levels and those for which no such delineation of discrete hierarchies is possible? That is, are systems of the second type in some practical sense more complex than those of the first type?
The second, and inter-related, set of questions is to do with systems far away from equilibrium. Specifically, is the failure of information-theoretic approaches when applied to far-from-steady-state systems (such as in ecology) true across complex dynamic systems in general? Can the inferential tools of information theory and info-metrics be modified and extended to provide insight into the dynamics of rapidly changing complex systems? Does the answer depend in any way on whether or not the system has discrete hierarchical levels of organization? Will the introduction of additional uncertainty about the constraints (information) be useful in that case?