Each time evolution processing is performed, an information recording unit records increase-decrease information indicating a type of partial program changed in number between pre- and post-evolution individuals and difference between fitness levels calculated from the pre- and post-evolution individuals in a storage unit. A probability setting unit determines, per partial program, a contribution level indicating how much a partial program contributes to increasing a fitness level, based on the information stored in the storage unit within a predetermined period and sets a selection probability per partial program in such a manner that a partial program having a higher contribution level is given a higher selection probability. When the evolution processing is performed, a generation processing unit selects a partial program to be included in the post-evolution individual in mutation processing according to the set selection probabilities.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A program generation apparatus comprising: a memory; and a processor configured to perform a procedure including: generating an image processing program by determining, based on genetic programming, a combination of partial programs to be included in the image processing program from a plurality of partial programs, the generating including evolution processing for evolving an individual formed by a combination of partial programs selected from the plurality of partial programs; recording, in the memory, information indicating a type of partial program that has been changed in number between pre- and post-evolution individuals and indicating difference between fitness levels calculated based on the pre- and post-evolution individuals, respectively, each time the evolution processing is performed; and determining, for each of the plurality of partial programs, a contribution level indicating how much an individual partial program contributes to increasing a fitness level, based on information accumulated in the memory within a predetermined time period and setting a selection probability for each of the plurality of partial programs in such a manner that a first partial program having a higher contribution level than a second partial program is given a higher setting value as a selection probability of the first partial program than the second partial program, wherein the evolution processing performed after the setting of the selection probability for each of the plurality of partial programs includes selecting a partial program to be included in a post-evolution individual in mutation processing from the plurality of partial programs according to selection probabilities set for respective ones of the plurality of partial programs. 2. The program generation apparatus according to claim 1, wherein the recording includes recording, each time the evolution processing is performed, an increased amount of fitness level, the increased amount being based on a value obtained by subtracting the fitness level based on the pre-evolution individual from the fitness level based on the post-evolution individual, in association with an individual type of a partial program that has been increased in number as a result of the evolution processing in the memory, and wherein the setting includes setting the selection probability per partial program, based on the increased amount of the fitness level per partial program accumulated in the memory within the predetermined time period. 3. The program generation apparatus according to claim 2, wherein, based on the increased amount of the fitness level per partial program accumulated in the memory within the predetermined time period, the setting includes determining the contribution level per partial program and removing a partial program whose contribution level determined is equal to or less than a predetermined value from selection targets in the evolution processing performed subsequently. 4. The program generation apparatus according to claim 2, wherein the increased amount of the fitness level is calculated by defining the value obtained by subtracting the fitness level based on the pre-evolution individual from the fitness level based on the post-evolution individual with the number of corresponding partial programs added in the post-evolution individual. 5. The program generation apparatus according to claim 1, wherein the procedure further includes: monitoring transition of a maximum fitness level calculated when the evolution processing is performed; and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in a post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities or randomly. 6. The program generation apparatus according to claim 1, wherein the plurality of partial programs are classified into a plurality of groups, based on similarity in processing content, and wherein the procedure further includes: monitoring transition of a maximum fitness level calculated when the evolution processing is performed; and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in a post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities from other partial programs that belong to a same group to which a partial program to be replaced in the pre-evolution individual belongs or from all the plurality of partial programs. 7. The program generation apparatus according to claim 1, wherein the plurality of partial programs are classified into groups in such a manner that partial programs that are used for a same kind of processing and that have different parameters set belong to a same group, and wherein the procedure further includes: monitoring transition of a maximum fitness level calculated when the evolution processing is performed; and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in the post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities from other partial programs that belong to a same group to which a partial program to be replaced in the pre-evolution individual belongs or from all the plurality of partial programs. 8. A program generation method comprising: generating, by a computer, an image processing program by determining, based on genetic programming, a combination of partial programs to be included in the image processing program from a plurality of partial programs, the generating including evolution processing for evolving an individual formed by a combination of partial programs selected from the plurality of partial programs; recording, by the computer, information indicating a type of partial program that has been changed in number between pre- and post-evolution individuals and indicating difference between fitness levels calculated based on the pre- and post-evolution individuals, respectively, in a memory, each time the evolution processing is performed; and determining, by the computer, for each of the plurality of partial programs, a contribution level indicating how much an individual partial program contributes to increasing a fitness level, based on information accumulated in the memory within a predetermined time period and setting a selection probability for each of the plurality of partial programs in such a manner that a first partial program having a higher contribution level than a second partial program is given a higher setting value as a selection probability of the first partial program than the second partial program, wherein the evolution processing performed after the setting of the selection probability for each of the plurality of partial programs includes selecting a partial program to be included in a post-evolution individual in mutation processing from the plurality of partial programs according to selection probabilities set for respective ones of the plurality of partial programs. 9. The program generation method according to claim 8, wherein, each time the evolution processing is performed, the recording includes recording an increased amount of the fitness level, the increased amount being based on a value obtained by subtracting the fitness level based on the pre-evolution individual from the fitness level based on the post-evolution individual, in association with an individual type of partial program that has been increased in number as a result of the evolution processing in the memory, and wherein, the setting include setting the selection probability per partial program, based on the increased amount of the fitness level per partial program accumulated in the memory within the predetermined time period. 10. The program generation method according to claim 9, wherein, the setting includes determining the contribution level per partial program, based on the increased amount of the fitness level per partial program accumulated in the memory within the predetermined time period, and removing a partial program whose contribution level determined is equal to or less than a predetermined value from selection targets in the evolution processing performed subsequently. 11. The program generation method according to claim 9, wherein the increased amount of the fitness level is calculated by defining the value obtained by subtracting the fitness level based on the pre-evolution individual from the fitness level based on the post-evolution individual with the number of corresponding partial programs added in the post-evolution individual. 12. The program generation method according to claim 8, further comprising: monitoring transition of a maximum fitness level calculated when the evolution processing is performed and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in a post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities or randomly. 13. The program generation method according to claim 8, wherein the plurality of partial programs are classified into a plurality of groups, based on similarity in processing content, and wherein the program generation method further includes: monitoring transition of a maximum fitness level calculated when the evolution processing is performed; and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in a post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities from other partial programs that belong to a same group to which a partial program to be replaced in the pre-evolution individual belongs or from all the plurality of partial programs. 14. The program generation method according to claim 8, wherein the plurality of partial programs are classified into groups in such a manner that partial programs that are used for a same kind of processing and that have different parameters set belong to a same group, and wherein the program generation method further includes: monitoring transition of a maximum fitness level calculated when the evolution processing is performed; and determining, based on an increase rate of the maximum fitness level, whether to select a partial program to be included in a post-evolution individual in mutation processing performed when the evolution processing performed subsequently is performed according to the selection probabilities from other partial programs that belong to a same group to which a partial program to be replaced in the pre-evolution individual belongs or from all the plurality of partial programs. 15. A non-transitory computer-readable storage medium storing a computer program that causes a computer to perform a procedure comprising: generating an image processing program by determining, based on genetic programming, a combination of partial programs to be included in the image processing program from a plurality of partial programs, the generating including evolution processing for evolving an individual formed by a combination of partial programs selected from the plurality of partial programs; recording information indicating a type of partial program that has been changed in number between pre- and post-evolution individuals and indicating difference between fitness levels calculated based on the pre- and post-evolution individuals, respectively, in a memory, each time the evolution processing is performed; and determining, for each of the plurality of partial programs, a contribution level indicating how much an individual partial program contributes to increasing a fitness level, based on information accumulated in the memory within a predetermined time period and setting a selection probability for each of the plurality of partial programs in such a manner that a first partial program having a higher contribution level than a second partial program is given a higher setting value as a selection probability of the first partial program than the second partial program, wherein the evolution processing performed after the setting of the selection probability for each of the plurality of partial programs includes selecting a partial program to be included in a post-evolution individual in mutation processing from the plurality of partial programs according to selection probabilities set for respective ones of the plurality of partial programs.