Robust Yet Fragile -- and DILO
(Deep Information from Limited
Observation)
Lori Parrott
Sandia National Laboratories
April 2012
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Forests are complex adaptive systems
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Other complex adaptive systems
•Power grids
•Biological
systems
•Social Networks
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Robust yet Fragile:
the Forest Fire Model
Time 1
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The forest evolves to adapt to
the most common threats.
Time 1
Time x
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Robust yet Fragile, and DILO
(Deep Information from Limited Observation)

Networks that evolve to improve their performance become
robust yet fragile.

Most of their features become robust, but a few remain fragile.

Details about the robust features are uninformative. Details
about the fragile features must be well understood.

Deep Information from Limited Observation is a concept that
can provide insights.
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With DILO you can infer far more about a system from
limited inquiries
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In summary, remember that
RYF and DILO are linked



Evolving complex systems –
whether organic or
engineered – display Robust
yet Fragile behavior.
Robust yet Fragile systems
can be understood through
DILO techniques. …
In other words, you can see
the forest for the trees
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