Generating levels for physics-based puzzle games with estimation of distribution algorithms
Lucas N. Ferreira, Claudio Fabiano Motta Toledo · 2014
This paper presents an estimation of distribution algorithm (EDA) to generate levels for physics-based puzzle games with the Angry Birds mechanics. The proposed EDA keeps three probability tables during its evolutionary process to sample new individuals that encode informations about the amount and placement of game objects inside the level. Sampled individuals are evaluated by a simulation-based fitness function, which considers the stability and the amount of the game objects inserted in a level. The best individual sampled from the probability tables is used to update them. Experiments indicated that the proposed EDA was capable of creating stable structures related to the Angry Bird gameplay.