Using Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity Functions
Lappoon R. Tang
Abstract:The Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for solving the benchmark problem of even-N-parity. Most approaches focus on improving the representation of individuals and/o… Show more
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