Symbolic Regression of Boolean Functions by Genetic Programming
Jir ́ iP osp ́ · 2013
An evolutionary metaphor of programming for a sym- bolic regression of Boolean functions, which represent logic circuits, is stud- ied. These functions are coded by acyclic oriented graphs with vertices cor- responding to elementary Boolean operations, e. g. negation, conjunction, disjunction (both inclusive and exclusive), and their negations. The used acyclic oriented graphs are represented by the so-called column tables. Ba- sic genetic operations of mutation and crossover are performed over these column tables. Preliminary results indicate that the proposed version of ge- netic programming with column tables is an effective evolutionary tool for a construction of optimized Boolean functions that are specified by tables of functional values for all possible combinations of arguments.