Procedural Content Generation using Behavior Trees (PCGBT)
This approach addresses the need for flexible and scalable content creation tools in game development, though it appears incremental as it adapts an existing method (behavior trees) to a new application area.
The paper tackles the problem of procedural content generation in games by using behavior trees to model game design agents, enabling modular and dynamic generation of levels and layouts for titles like Super Mario Bros., Mega Man, and Metroid.
Behavior trees (BTs) are a popular method for modeling NPC and enemy AI behavior and have been widely used in commercial games. In this work, rather than use BTs to model game playing agents, we use them for modeling game design agents, defining behaviors as content generation tasks rather than in-game actions. Similar to how traditional BTs enable modeling behaviors in a modular and dynamic manner, BTs for PCG enable simple subtrees for generating parts of levels to be combined modularly to form complex trees for generating whole levels as well as generators that can dynamically vary the generated content. We refer to this approach as Procedural Content Generation using Behavior Trees, or PCGBT, and demonstrate it by using BTs to model generators for Super Mario Bros., Mega Man and Metroid levels as well as dungeon layouts and discuss several ways in which this paradigm could be applied and extended in the future.