propeller.problems.valiant
Possibly impossible to solve with genetic programming. Stems from the work of Leslie Valiant and involves determining the parity of an unknown subsequence of a larger sequence of bits.
-main
(-main & args)
Runs the top-level genetic programming function, giving it a map of arguments with defaults that can be overridden from the command line or through a passed map.
error-function
(error-function argmap data individual)
Finds the behaviors and errors of an individual: Error is 0 if the value and the program’s selected behavior match, or 1 if they differ. The behavior is here defined as the final top item on the BOOLEAN stack.
instructions
A list of instructions which includes keyword strings with the format “in + i” where i is a number from 0 to num-vars-1 concatenated with boolean and exec_if instructions and close.
train-and-test-data
Inputs are num-train
random boolean values and outputs are the even parity of a subset of input variables.