Firas Safadi explains, “My contribution has been to consider games as a collection of independent conceptual problems. It is necessary to completely separate the development of these games and the development of AI. Game developers must continue to develop them but must do so without worrying about the AI part while AI developers are going to do it without knowing which game this AI will be used in! The mistake that has been made to date has been to want to standardize AI solutions and to try to develop standard AI systems for the conceptual problems they encountered”. Raphael Fonteneau continues, “If we want to make an analogy, we could take the example of the Android platform, an open-source mobile operating system developed independently of the phones in which it is installed. This is similar to what we have done here for video games: creating a platform to which everyone can contribute”.

The researchers from Liège have developed a conceptual middleware prototype; they then rewrote the code for a video game to which they had access but by adopting the separation between AI and video game and inserting a conceptual middleware between them, between the algorithm of the AI and the game part, so to speak. They then took another very different game and succeeded in using AI modules developed for the first game in the second game. In the latter case, the middleware was simply completed (and not totally modified) because it was made to measure for the requirements of the first game. Of course, in its definitive form, this middleware should no longer need to be completed (or at least barely so) because it should take into account the requirements of most games. It was thereby shown that very little effort was required to make use of this middleware in another game.

Contribution of video games

This also shows how games can help AI research. It is a field that is mostly driven by tests, by trial and error. Before the development of video games, tests were quite simple: chess, the game of go, queens or small artificial games that researchers constructed for the purpose in hand. But there were no environments that were similar to those in which human beings evolve. These are environments that require far greater cognitive faculties than those used to solve a game of chess, for example. Today, thanks to games, researchers can test their AI algorithms in environments which are similar to those in which human beings evolve. "And this has really changed the speed of development of new AIs, it has accelerated the process. If we take the example of Deep Mind based in London, which has been bought over by Google whose objective is to create the first real AI by using technologies close to those developed here: this company has institutionalized the video game as an experimental platform for its researchers in order to construct the first universal AI as portrayed by the intelligent robots that appear in movies...for now this is still science-fiction but not for much longer"! Explains Damien Ernst.