Artificial Intelligence in Video Games: Towards a Unified Framework

With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of complex environments is pressing. Since video game AI is often specifically designed for each game, video game AI tools currently focus on allowing video game developers to quickly and efficiently create specific AI. One issue with this approach is that it does not efficiently exploit the numerous similarities that exist between video games not only of the same genre, but of different genres too, resulting in a difficulty to handle the many aspects of a complex environment independently for each video game. Inspired by the human ability to detect analogies between games and apply similar behavior on a conceptual level, this paper suggests an approach based on the use of a unified conceptual framework to enable the development of conceptual AI which relies on conceptual views and actions to define basic yet reasonable and robust behavior. The approach is illustrated using two video games, Raven and StarCraft: Brood War.