evolving player-specific content for level based arcade games
In this poster, we attempt to generate content for single player level based arcade games, according to the player's skill. The objective is to make the game just enough challenging for the player. An evolvable representation of the game content is developed. The player's performance is measured after completion of each level. An Artificial Neural Network (ANN) is used to estimate the expected performance for the level content. The deviation of the actual performance of the player from the expected performance is used to estimate the toughness of the next level. A Genetic Algorithm then evolves the next level. The fittest candidate is the one matching the required toughness.
content creation player entertainment evolution