Blurb:: Specification of an hierarchy of model fidelities, ordered from
low to high.

Description:: A hierarchical surrogate model manages an ordered set of
model fidelities, each of which may in turn involve multiple discretization
levels (in the case of a simulation model) or additional model recursions.

The ordering is assumed to be from lowest fidelity to highest
fidelity, as dictated by an accuracy versus cost trade-off.
Corresponding sequence specifications within methods (e.g., \c
quadrature_order_sequence, \c sparse_grid_level_sequence, \c
expansion_order_sequence, etc. within stochastic expansion methods)
should be synchronized with this model order.

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<b> Additional Discussion </b>

Internal to the model, only one low fidelity model instance and one
high fidelity model instance are active at any given time, although
various optimization and UQ algorithms can be used to traverse deep
multilevel and multifidelity hierarchies by activating different model
combinations and different response modes within the hierarchical model
infrastructure.

Topics::
Examples::
\verbatim
model,
	id_model = 'HIERARCH'
	surrogate hierarchical
	  ordered_model_fidelities = 'LF' 'MF 'HF'
	  correction additive zeroth_order

model,
	id_model = 'LF'
	simulation
	  interface_pointer = 'LF_DRIVER'

model,
	id_model = 'MF'
	simulation
	  interface_pointer = 'MF_DRIVER'

model,
	id_model = 'HF'
	simulation
	  interface_pointer = 'HF_DRIVER'
\endverbatim

Theory::
Faq::
See_Also:: method-multilevel_sampling, method-polynomial_chaos, method-stoch_collocation, method-surrogate_based_local
