Blurb::
Cost estimates associated with a set of solution control values.

Description:: 
Simulation-based models may have an associated \c solution_level_control,
which identifies a hierarchy of solution states, such as a set of mesh
discretizations from coarse to fine, a set of solver tolerances from
loose to tight, etc.  In algorithms that manage such a hierarchy and
perform optimal resource allocation among the solution states (e.g., 
multilevel Monte Carlo), it is important to estimate a set of costs 
associated with each state.  These cost estimates can be relative,
such as in the example below (lowest cost normalized to 1.)

<b>Note:</b> a scalar solution cost can be specified without an associated 
solution level control.  This is useful when employing a hierarchy of
model forms (each model has a scalar solution cost and no solution level
control) instead of a hierarchy of discretization levels (one model has 
a vector-valued solution cost associated with multiple solution levels).

Topics::

Examples::
\verbatim
model,
	simulation
	  solution_level_control = 'mesh_size'
	  solution_level_cost = 1. 8. 64. 512. 4096.

variables,
	uniform_uncertain = 9
	  lower_bounds      =  9*-1.
	  upper_bounds      =  9* 1.
	discrete_state_set
	  integer = 1
      	  set_values = 4 8 16 32 64
      	  descriptors = 'mesh_size'
\endverbatim

Theory::
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