Patent ID: 11972842
Assignee: NATURAL COMPUTATION LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 20:
21. A computer system for generating data visualizations comprising:
one or more processors; and
memory;
wherein the memory stores instructions executed by the one or more processors, and the instructions for:
obtaining a parent population with programs that encode functions;
obtaining a list of randomly generated test inputs;
generating a target dataset that includes initial input-output pairs of randomly generated binary strings;
applying a fitness function to assign a fitness score to each program in the parent population, wherein the fitness score represents at least an ability of a respective program in the parent population to match the initial input-output pairs of the target dataset;
initializing a seed list with copies of the program in the parent population that satisfy a novelty condition, wherein the novelty condition is representative of an ability of a program to produce distinct and unique output for the list of randomly generated test inputs;
determining if a terminating condition of the seed list has been satisfied, wherein the terminating condition is representative of an ability of one or more programs in the seed list to solve one or more genetic programming instances;
in accordance with a determination that the terminating condition has not been satisfied:
applying at least one genetic operator to the parent population to obtain a current offspring population of programs, wherein the at least one genetic operator includes operators applied to the parent population to grow the seed list, based on fitness scores of the programs in the parent population, to solve the one or more genetic programming instances; and
repeating steps of:
generating a new target dataset that includes new input-output pairs of randomly generated binary strings;
applying the fitness function to assign a new fitness score to each program in the current offspring population, wherein the new fitness score represents at least an ability of a respective program in the current offspring population to match the new input-output pairs of the new target dataset;
appending, to the seed list, copies of the programs in the current offspring population that satisfy said novelty condition; and
applying the at least one genetic operator to the current offspring population to obtain a new offspring population of programs and setting the new offspring population of programs as the current offspring population;

until said termination condition is satisfied.