Tanager: A Generator of Feasible and Engaging Levels for Angry Birds

Generating feasible levels for physics-based puzzle games is a complex and time-consuming task. This is because the mechanics of these games are based on realistic physics, so simulations are required to evaluate the playability of the generated levels. Recently, a few generators have been able to produce considerably complex levels in the context of the Angry Birds game, a very famous title of this genre. However, none of these generators are able to guarantee the playability of their produced levels. This paper presents Tanager, a level generator based on a genetic algorithm that is capable of producing feasible levels for the Angry Birds game. Evaluating playability in this game requires checking both the stability of the stacked blocks and the possibility of killing all the pigs with the given amount of birds. These two components are handled by the algorithm through a simulation. The first one is calculated by measuring the overall velocity of the blocks and the second is defined by an intelligent agent, which plays the levels. Three sets of experiments are conducted to evaluate Tanager. The first one measures the performance of the genetic algorithm underneath Tanager. The second one explores the expressivity of the generated levels considering their structural characteristics. The third one measures design quality of levels via an online user study. Results show that Tanager is capable of generating a considerable variety of feasible levels that are as engaging and enjoyable as those manually designed. However, the generated levels are less challenging than the hand-authored ones.