Increasing Generality in Machine Learning through Procedural Content Generation

Understand

Procedural Content Generation (PCG) refers to the practice, in videogames and other games, of generating content such as levels, quests, or characters algorithmically.

• Motivated by the need to make games replayable, as well as to reduce authoring burden, limit storage space requirements, and enable particular aesthetics, a large number of PCG methods have been devised by game developers.
• Additionally, researchers have explored adapting methods from machine learning, optimization, and constraint solving to PCG problems.
• Games have been widely used in AI research since the inception of the field, and in recent years have been used to develop and benchmark new machine learning algorithms.