Deep information from limited observation of robust yet fragile systems

Randall A. LaViolette, Kristin Glass and Richard Colbaugh

Physica A: Statistical Mechanics and its Applications, 2009, vol. 388, issue 17, 3283-3287

Abstract: We show how one can completely reconstruct even moderately optimized configurations of the Forest Fire model with relatively few observations. We discuss the relationship between the deep information from limited observations (DILO) to the robust-yet-fragile (RYF) property of the Forest Fire model and propose that DILO may be a general property of RYF complex systems.

Keywords: Random systems; Complex systems; Robust yet fragile; Deep information; Limited observations; Vulnerability (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:388:y:2009:i:17:p:3283-3287

DOI: 10.1016/j.physa.2009.05.019

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