Modeling Emotional Mutation and Evolvement Using Genetic Algorithm in Agency
Human mind has the ability to generate emotions based on internal and external environment. These emotions are based on past experiences and the current situation. Mutation of emotions in human is the change in the intensity of emotion and the more intense the emotion is, it has more chances of existence. In mutative state two emotions are crossover and from the new emotions only the fittest and strongest emotion survive. Emotional mutation and evolvement helps human mind in decision making and in generating response. In agency the phenomenon of emotional modeling can be accomplished by Mutation and Evolvement for generating output. Genetic algorithm is computational model that is inspired by evolution of biological population and by using mutation and crossover of Genetic Algorithm the agency is able to generate output.
This paper presents the algorithmic approach for emotional Mutation and Evolvement using Genetic Algorithm for generating output in agency.