Changes between Version 11 and Version 12 of Features/Genetic Programming

Timestamp:

07/08/12 04:07:53 (12 years ago)

Author:

swagner

Comment:

--

Features/Genetic Programming

@@ -6 +6 @@
 !HeuristicLab supports tree-based (Koza-style) genetic programming. This classical form of genetic programming uses a tree data structure as representation of solution candidates. The data types and operators to work with tree-based solution candidates are implemented in the plugin `HeuristicLab.Encodings.SymbolicExpressionTree`. 
 
-Supported operators (in 3.3.6):
+Supported operators (in 3.3.6 and above):
  * Full tree creator
  * Grow tree creator
@@ -21 +21 @@
 The symbolic expression tree encoding contains the implementation of the problem independent data structure (a tree of symbols) and operators. Based on the encoding we implemented three well-known GP problems.
 
-Supported Problems (in 3.3.6):
+Supported Problems (in 3.3.6 and above):
  * Symbolic regression (`HeuristicLab.Problems.DataAnalysis.Symbolic.Regression`)
  * Symbolic classification (`HeuristicLab.Problems.DataAnalysis.Symbolic.Classification`)
@@ -103 +103 @@
 We also provide an implementation for automatically defined functions (ADFs) as described by Koza. Automatically defined functions allow to extract useful code fragments into a separate function which can be called multiple times either while executing the result producing branch or another ADF. ADFs are created and manipulated by architecture altering operators while evolving genetic programming solutions. This means ADFs underlie selection pressure in the same way as the main result producing branch and the evolutionary process determines if ADFs survive in the final population and which code fragments are moved to ADFs.   
 
-Supported architecture altering operators (3.3.6)
+Supported architecture altering operators (in 3.3.6 and above)
  * Subroutine creater
  * Subroutine deleter