[ecspy] r117 committed - Modified the documentation to more clearly explain the purpose of boun...
ec...@googlecode.com
Author: aaron.lee.garrett
Date: Tue Oct 4 07:31:53 2011
Log: Modified the documentation to more clearly explain the purpose of
bounding functions.
http://code.google.com/p/ecspy/source/detail?r=117
Modified:
/trunk/ecspy/ec.py
=======================================
--- /trunk/ecspy/ec.py Sun Aug 22 00:13:44 2010
+++ /trunk/ecspy/ec.py Tue Oct 4 07:31:53 2011
@@ -43,6 +43,24 @@
``upper_bound`` argument is ``None``, the Bounder leaves
the candidate unchanged (which is the default behavior).
+ A bounding function is necessary to ensure that all
+ evolutionary operators respect the legal bounds for
+ candidates. If the user is using only custom operators
+ (which would be aware of the problem constraints), then
+ those can obviously be tailored to enforce the bounds
+ on the candidates themselves. But the built-in operators
+ make only minimal assumptions about the candidate solutions.
+ Therefore, they must rely on an external bounding function
+ that can be user-specified (so as to contain problem-specific
+ information). As a historical note, ECsPy was originally
+ designed to require the maximum and minimum values for all
+ components of the candidate solution to be passed to the
+ ``evolve`` method. However, this was replaced by the bounding
+ function approach because it made fewer assumptions about
+ the structure of a candidate (e.g., that candidates were
+ going to be lists) and because it allowed the user the
+ flexibility to provide more elaborate boundings if needed.
+
In general, a user-specified bounding function must accept
two arguments: the candidate to be bounded and the keyword
argument dictionary. Typically, the signature of such a
@@ -284,7 +302,8 @@
This function creates a population and then runs it through a
series
of evolutionary epochs until the terminator is satisfied. The
general
outline of an epoch is selection, variation, evaluation,
replacement,
- migration, archival, and observation. The function returns the
individuals
+ migration, archival, and observation. The function returns a list
of
+ elements of type ``Individual`` representing the individuals
contained
in the final population.
Arguments: