1Blurb:: Portion of batch size dedicated to exploration
2
3Description:: Refinement candidates are generated by an acquisition
4function such as maximum expected improvement, which balances
5exploration and exploitation.  Refinement candidates can also be
6generated by purely explorative metrics such as maximum prediction
7variance.  For a specified \c batch_size, \c exploration specifies the
8subset of this total that will be dedicated to pure exploration of the
9parameter space.
10
11<b> Default Behavior </b>
12All of the batch size is devoted to the standard acquisition approach,
13balancing exploration and exploitation .
14
15Topics::
16
17Examples::
18\verbatim
19method,
20        efficient_global
21	  seed = 1237
22	  batch_size = 8	# total
23	  exploration = 2	# 2 out of 8
24\endverbatim
25
26Theory::
27Faq::
28See_Also::
29