.. _method-efficient_global-batch_size: """""""""" batch_size """""""""" Total batch size in parallel EGO .. toctree:: :hidden: :maxdepth: 1 method-efficient_global-batch_size-exploration method-efficient_global-batch_size-synchronization **Specification** - *Alias:* None - *Arguments:* INTEGER **Child Keywords:** +-------------------------+--------------------+---------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+=====================+=============================================+ | Optional | `exploration`__ | Portion of batch size dedicated to | | | | exploration in parallel EGO | +----------------------------------------------+---------------------+---------------------------------------------+ | Optional | `synchronization`__ | Select how Dakota schedules a batch of | | | | concurrent function evaluations in a | | | | parallel algorithm | +----------------------------------------------+---------------------+---------------------------------------------+ .. __: method-efficient_global-batch_size-exploration.html __ method-efficient_global-batch_size-synchronization.html **Description** Refinement candidates are generated by an acquisition function such as maximum expected improvement, which balances exploration and exploitation. Refinement candidates can also be generated by purely explorative metrics such as maximum prediction variance. For a specified ``batch_size``, ``exploration`` specifies the subset of this total that will be dedicated to pure exploration of the parameter space. *Default Behavior* All of the batch size is devoted to the standard acquisition approach, balancing exploration and exploitation. **Examples** .. code-block:: method, efficient_global seed = 1237 batch_size = 8 # total exploration = 2 # 2 out of 8