An Evolutionary Algorithm was run in real-time for the procedural generation of enemies in a third-person, wave based hack and slash and shoot 'em up game. The algorithm evaluates enemies as individuals based on their effectiveness at battling the player character. Every generation is presented as a new wave of enemies whose properties have been adjusted according to the fitness of the last wave. By constantly making new enemies more adept at the task of the defeating the current player, I attempt to automatically and naturally raise the difficulty as the game progresses. The goal is also to improve player satisfaction as a result. By analyzing the response from players and observing the changes of the generated enemies, I determine whether or not this is an appropriate implementation of Evolutionary Algorithms. Results showed that the success of the algorithm varied substantially between tests, giving a number of both failed and successful tests. I go through some of the individual data and draw conclusions on what specific conditions makes the algorithm perform desirably.