1. A method of generating robot genome, the method comprising: a user preference receiving process, wherein user preferences are received from a user, the user preferences including internal state attribute preferences of internal state attributes according to external stimuli and behavior preferences distinguished according to the internal state attributes; a robot genome group generating process, wherein a robot genome group is generated, the robot genome group including a plurality of robot genomes containing initial values of internal state related genes generated by reflecting the internal state attribute preferences, initial values of behavior decision related genes generated by reflecting the behavior preferences, and initial values of essential element related genes determined according to conditions; a masking process, wherein internal state related genes and behavior decision related genes manifested with respect to external stimuli and manifested behaviors are determined from among the genes by applying a masking table to each of the plurality of robot genomes, and a determination is made whether manifestation attributes of the genes determined to manifest are positive or negative; a manifesting process, wherein each of the robot genomes is manifested according to a stimulus scenario for testing whether the robot genomes are suitable for the input user preferences, and manifestation results of the robot genomes according to the stimulus scenario are output; a suitability determining process, wherein a reliability value of each robot genome is determined by receiving the manifestation results according to the stimulus scenario and the robot genomes, and a determination is made whether reliability values of robot genomes extracted from the robot genome group are suitable for the user preferences; a modifying process, wherein the extracted robot genomes are modified according to a modification method when the reliability values of the extracted robot genomes are not suitable for the user preferences according to a determination result in the suitability determining process; a secondary robot genome group generating process, wherein a new robot genome group is generated, which includes a plurality of new robot genomes in which the internal state attribute preferences and the behavior preferences are reflected and the modified robot genomes; and an iterating process, wherein the masking process, the manifesting process, and the suitability determining process are iteratively performed for the secondary robot genome group, and the modifying process and the secondary robot genome group generating process are iteratively performed according to a result in the suitability determining process.