Adaptation using hybridized genetic crossover strategies

We present a simple game which mimics the complex dynamics found in many natural and social systems. Players modify their strategies periodically, depending on their performances. We propose that the agents use hybridized one-point genetic crossover mechanism, inspired by genetic evolution in biology, to modify the strategies and replace the bad strategies. We study the performances of the agents under different conditions and investigate how they adapt themselves in order to survive or be the best, by finding new strategies using the highly effective mechanism we proposed. We introduce the measure of total utility of the system and use it to study the efficiency and dynamics of the game.