Dakota Reference Manual: unordered_model_fidelities

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unordered_model_fidelities

Specification of an unordered ensemble of low-fidelity approximations

## Specification

Alias: approximation_models

Argument(s): STRINGLIST

## Description

A `non_hierarchical` surrogate model manages an unordered set of low-fidelity model approximations, each of which may include hyper-parameter resolution controls (in the case of a simulation model) or additional model recursions.

Any corresponding sequence specifications within methods (e.g., `quadrature_order_sequence`, `sparse_grid_level_sequence`, `expansion_order_sequence`, etc. within stochastic expansion methods) should be synchronized with the order in the model listing.

Internal to the non-hierarchical model, subsets of the model ensemble may be active for any given evaluation, as dictated by the iterative algorithm in use.

## Examples

    model,
        id_model = 'NONHIERARCH'
        surrogate non_hierarchical
          unordered_model_fidelities = 'LF1' 'LF2'
          truth_model_pointer = 'HF'

    model,
        id_model = 'LF1'
        simulation
          interface_pointer = 'LF1_DRIVER'
              solution_level_cost = 1.

    model,
        id_model = 'LF2'
        simulation
          interface_pointer = 'LF2_DRIVER'
              solution_level_cost = 2.4

    model,
        id_model = 'HF'
        simulation
          interface_pointer = 'HF_DRIVER'
              solution_level_cost = 256.

## See Also

These keywords may also be of interest:

- hierarchical