A search-based approach for generating Angry Birds levels

This paper presents a genetic algorithm (GA) for the procedural generation of levels in the Angry Birds game. The GA evaluates the levels based on a simulation which measures the elements´ movement during a period of time. The algorithm´s objective is to minimize this metric to generate stable structures. The level evaluation also considers some restrictions, leading the levels to have certain characteristics. Since there is no open source code of the game, a game clone has been developed independently of our algorithm. This implementation can be used to support experiments with procedural content generation (PCG) methods for this game type. We performed experiments in order to evaluate the expressivity of the level generator and the results showed that the proposed algorithm could generate levels with interesting stable structures.